Show Code
pacman::p_load(jsonlite, tidyverse, ggtext,
knitr, lubridate, patchwork,
ggraph, tidygraph, igraph,
ggiraph, kableExtra, plotly, fmsb)Methodology and Analysis
1 Overview
This exercise will target to answer one of the three challenges from VAST 2025 which features a fictitious island nation, Oceanus, famous for fishing and quiet seaside communities.
The chosen challenge is Mini-Challenge 1.
1.1 Background
One of music’s biggest superstars is Oceanus native Sailor Shift. From humble beginnings, Sailor has grown in popularity and now enjoys fans around the world. Sailor started her career on the island nation of Oceanus which can be clearly seen in her early work, she started in the genre of “Oceanus Folk”. While Sailor has moved away from the traditional Oceanus style, the Oceanus Folk has made a name for itself in the musical world. The popularity of this music is one of the factors driving an increase in tourism to a quiet island nation that used to be known for fishing.
In 2023, Sailor Shift joined the Ivy Echoes – an all-female Oceanus Folk band consisting of Sailor (vocalist), Maya Jensen (vocalist), Lila “Lilly” Hartman (guitarist), Jade Thompson (drummer), and Sophie Ramirez (bassist). They played together at venues throughout Oceanus but had broken up to pursue their individual careers by 2026. Sailor’s breakthrough came in 2028 when one of her singles went viral, launched to the top of the global charts (something no other Oceanus Folk song had ever done). Since then, she has only continued to grow in popularity worldwide.
Sailor has released a new album almost every year since her big break, and each has done better than the last. Although she has remained primarily a solo artist, she has also frequently collaborated with other established artists, especially in the Indie Pop and Indie Folk genres. She herself has branched out musically over the years but regularly returns to the Oceanus Folk genre — even as the genre’s influence on the rest of the music world has spread even more.
Sailor has always been passionate about two things: (1) spreading Oceanus Folk, and (2) helping lesser-known artists break into music. Because of those goals, she’s particularly famous for her frequent collaborations.
Additionally, because of Sailor’s success, more attention began to be paid over the years to her previous bandmates. All 4 have continued in the music industry—Maya as an independent vocalist, Lilly and Jade as instrumentalists in other bands, and Sophie as a music producer for a major record label. In various ways, all of them have contributed to the increased influence of Oceanus folk, resulting in a new generation of up-and-coming Oceanus Folk artists seeking to make a name for themselves in the music industry.
Now, as Sailor returns to Oceanus in 2040, a local journalist – Silas Reed – is writing a piece titled Oceanus Folk: Then-and-Now that aims to trace the rise of Sailor and the influence of Oceanus Folk on the rest of the music world. He has collected a large dataset of musical artists, producers, albums, songs, and influences and organized it into a knowledge graph. Your task is to help Silas create beautiful and informative visualizations of this data and uncover new and interesting information about Sailor’s past, her rise to stardom, and her influence.
1.2 Tasks and Questions
Design and develop visualizations and visual analytic tools that will allow Silas to explore and understand the profile of Sailor Shift’s career
- Who has she been most influenced by over time?
- Who has she collaborated with and directly or indirectly influenced?
- How has she influenced collaborators of the broader Oceanus Folk community?
Develop visualizations that illustrate how the influence of Oceanus Folk has spread through the musical world.
- Was this influence intermittent or did it have a gradual rise?
- What genres and top artists have been most influenced by Oceanus Folk?
- On the converse, how has Oceanus Folk changed with the rise of Sailor Shift? From which genres does it draw most of its contemporary inspiration?
Use your visualizations to develop a profile of what it means to be a rising star in the music industry.
- Visualize the careers of three artists. Compare and contrast their rise in popularity and influence.
- Using this characterization, give three predictions of who the next Oceanus Folk stars with be over the next five years.
1.3 Data Source
The data for this exercise is from VAST 2025 MC1.
1.4 Data Description
Graph Description
- Directed Multigraph
- Number of nodes: 17,412
- Number of edges: 37,857
- 18 connected components
- Node types are: {Person, Song, RecordLabel, Album, MusicalGroup}
- Edge types are: {MemberOf, PerformerOf, ComposerOf, ProducerOf, LyricistOf, InStyleOf, InterpolatesFrom, CoverOf, LyricalReferenceTo, DirectlySamples, RecordedBy, DistributedBy}
- The graph format is a JSON file. The root-level JSON object consists of graph-level properties specifying that it is directed and a multigraph, a “nodes” key which holds the list of nodes, and a “links” key which holds the list of edges.
The data for this challenge comes from two different sources:
- an online, crowdsourced repository of musical influence, where contributors have manually notated instances in which songs or albums have sampled, covered, or otherwise drawn inspiration from previous work.
- aggregate-level descriptions of song popularity, as labeled by our journalist, Silas Reed. These notations (notable and notoriety_date) are directly based on both the number of sales and streams that the song/album has achieved as well as the whether or not the work landed on a top record chart.
1.5 Install and Load the Required Libraries
The following libraries are used in this exercise and the code below loads them into the working environment.
Utility Tools
- jsonlite: To parse JSON
- tidyverse - Data science tools
- ggtext - Tools for text formatting
- knitr - For better table displays
- lubridate - For processing date and time
- kableExtra - For tabular properties
Graphing Tools
- patchwork - For combining ggplot plots
- ggraph - For plotting network data
- tidygraph - For graph manipulations
- igraph - Contains functions for network analysis
- ggiraph - Interactive plots
- plotly - Professional visualisations
1.6 Importing Data
For the purpose of this exercise, a data file called MC1_graph will be used. The code below imports MC1_graph.json into R environment by using fromJSON() function of jsonlite package.
Show Code
mc1_data <- fromJSON("data/MC1_graph.json")
glimpse(mc1_data)List of 5
$ directed : logi TRUE
$ multigraph: logi TRUE
$ graph :List of 2
..$ node_default: Named list()
..$ edge_default: Named list()
$ nodes :'data.frame': 17412 obs. of 10 variables:
..$ Node Type : chr [1:17412] "Song" "Person" "Person" "Person" ...
..$ name : chr [1:17412] "Breaking These Chains" "Carlos Duffy" "Min Qin" "Xiuying Xie" ...
..$ single : logi [1:17412] TRUE NA NA NA NA FALSE ...
..$ release_date : chr [1:17412] "2017" NA NA NA ...
..$ genre : chr [1:17412] "Oceanus Folk" NA NA NA ...
..$ notable : logi [1:17412] TRUE NA NA NA NA TRUE ...
..$ id : int [1:17412] 0 1 2 3 4 5 6 7 8 9 ...
..$ written_date : chr [1:17412] NA NA NA NA ...
..$ stage_name : chr [1:17412] NA NA NA NA ...
..$ notoriety_date: chr [1:17412] NA NA NA NA ...
$ links :'data.frame': 37857 obs. of 4 variables:
..$ Edge Type: chr [1:37857] "InterpolatesFrom" "RecordedBy" "PerformerOf" "ComposerOf" ...
..$ source : int [1:37857] 0 0 1 1 2 2 3 5 5 5 ...
..$ target : int [1:37857] 1841 4 0 16180 0 16180 0 5088 14332 11677 ...
..$ key : int [1:37857] 0 0 0 0 0 0 0 0 0 0 ...2 Data Pre-Processing
2.1 Split into Nodes and Edges
The mc1_data.json data file provided by VAST 2025 for Mini-Challenge 1 consists of both nodes and links. The following codes will be used to split them into individual files for easier data matriculation.
2.1.1 Get Nodes
Show Code
mc1_nodes_raw <- as_tibble(mc1_data$nodes)The first 5 rows of mc1_nodes_raw are shown below.
Show Code
kable(head(mc1_nodes_raw, 5))| Node Type | name | single | release_date | genre | notable | id | written_date | stage_name | notoriety_date |
|---|---|---|---|---|---|---|---|---|---|
| Song | Breaking These Chains | TRUE | 2017 | Oceanus Folk | TRUE | 0 | NA | NA | NA |
| Person | Carlos Duffy | NA | NA | NA | NA | 1 | NA | NA | NA |
| Person | Min Qin | NA | NA | NA | NA | 2 | NA | NA | NA |
| Person | Xiuying Xie | NA | NA | NA | NA | 3 | NA | NA | NA |
| RecordLabel | Nautical Mile Records | NA | NA | NA | NA | 4 | NA | NA | NA |
2.1.2 Get Edges
Show Code
mc1_edges_raw <- as_tibble(mc1_data$links)The first 5 rows of mc1_edges_raw are shown below.
Show Code
kable(head(mc1_edges_raw, 5))| Edge Type | source | target | key |
|---|---|---|---|
| InterpolatesFrom | 0 | 1841 | 0 |
| RecordedBy | 0 | 4 | 0 |
| PerformerOf | 1 | 0 | 0 |
| ComposerOf | 1 | 16180 | 0 |
| PerformerOf | 2 | 0 | 0 |
2.2 Data Overview
Before proceeding to data pre-processing, we examine the data to gain a clearer understanding of the dataset and to verify the structural integrity of the imported graph.
In this code chunk below, ggplot2 functions are used the reveal the frequency distribution of Node Type field of mc1_nodes_raw and Edge Type field of mc1_edges_raw.
Show Code
# Plot 1: Node Types
p1 <- ggplot(
mc1_nodes_raw,
aes(y = fct_infreq(`Node Type`), fill = `Node Type`)
) +
geom_bar() +
scale_fill_brewer(palette = "Set3") +
labs(title = "Node Types", x = "Count", y = "Node Type") +
theme_minimal() +
theme(legend.position = "none")
# Plot 2: Edge Types
p2 <- ggplot(
mc1_edges_raw,
aes(y = fct_infreq(`Edge Type`), fill = `Edge Type`)
) +
geom_bar() +
scale_fill_brewer(palette = "Set3") +
labs(title = "Edge Types", x = "Count", y = "Edge Type") +
theme_minimal() +
theme(legend.position = "none")
# Combine side by side
p1 + p2
2.3 Adding Identifying Columns
There are 2 columns that provides information on names, the name and stage_name column. The code below shows that the name column is the one that contains information on our target of interest Sailor Shift.
Show Code
kable(mc1_nodes_raw %>%
filter(grepl("Sailor Shift", name))) #Sailor Shift is in name column and not in stage_name column| Node Type | name | single | release_date | genre | notable | id | written_date | stage_name | notoriety_date |
|---|---|---|---|---|---|---|---|---|---|
| Person | Sailor Shift | NA | NA | NA | NA | 17255 | NA | NA | NA |
Show Code
kable(mc1_nodes_raw %>%
filter(grepl("Ivy Echos", name))) #Ivy Echos is also in name column and not in stage_name column| Node Type | name | single | release_date | genre | notable | id | written_date | stage_name | notoriety_date |
|---|---|---|---|---|---|---|---|---|---|
| MusicalGroup | Ivy Echos | NA | NA | NA | NA | 17260 | NA | NA | NA |
Identifying columns for Sailor Shift, Ivy Echos and Oceanus Folk are added to aid in the identification and filtering of these key variables for further analysis.
Show Code
mc1_nodes_raw <- mc1_nodes_raw %>%
mutate(
is_sailor = (
str_detect(name, regex("sailor shift", ignore_case = TRUE))
) %>% replace_na(FALSE),
is_ivy = (
str_detect(name, regex("ivy echos", ignore_case = TRUE))
) %>% replace_na(FALSE),
is_oceanus_folk = str_detect(genre, regex("oceanus folk", ignore_case = TRUE)) %>% #na/not oceanus folk = false
replace_na(FALSE)
)
kable(head(mc1_nodes_raw,5))| Node Type | name | single | release_date | genre | notable | id | written_date | stage_name | notoriety_date | is_sailor | is_ivy | is_oceanus_folk |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Song | Breaking These Chains | TRUE | 2017 | Oceanus Folk | TRUE | 0 | NA | NA | NA | FALSE | FALSE | TRUE |
| Person | Carlos Duffy | NA | NA | NA | NA | 1 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qin | NA | NA | NA | NA | 2 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xie | NA | NA | NA | NA | 3 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Nautical Mile Records | NA | NA | NA | NA | 4 | NA | NA | NA | FALSE | FALSE | FALSE |
2.4 Convert Date Fields
The columns related to date are in char format and will be converted to int using the code below.
Note: Dates only appears in Songs and Albums.
Show Code
mc1_nodes_raw <- mc1_nodes_raw %>%
mutate(across(c(release_date, notoriety_date, written_date),
~as.integer(if_else(`Node Type` %in% c("Song", "Album"), ., NA_character_))))2.5 Check and Fix Duplicates
2.5.1 Duplicates in Nodes
For Nodes, there are no duplicated id.
Show Code
mc1_nodes_raw %>%
count(id) %>%
filter(n > 1)# A tibble: 0 × 2
# ℹ 2 variables: id <int>, n <int>The following code chunk shows a total of 4,953 records with duplicated names in mc1_nodes_raw.
Show Code
duplicated_name <- mc1_nodes_raw %>%
count(name) %>%
filter(n > 1)
kable(head(duplicated_name,5))| name | n |
|---|---|
| Agata Records | 2 |
| Ancestral Echoes | 2 |
| Angela Thompson | 2 |
| Anthony Davis | 2 |
| Anthony Smith | 2 |
Show Code
cat("Total number of duplicated name:", sum(duplicated_name$n), "\n")Total number of duplicated name: 4953 The table below shows some of the duplicated name.
Show Code
mc1_nodes_raw %>%
filter(name %in% duplicated_name$name) %>%
arrange(name) %>%
kable() %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "200px")| Node Type | name | single | release_date | genre | notable | id | written_date | stage_name | notoriety_date | is_sailor | is_ivy | is_oceanus_folk |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| RecordLabel | Agata Records | NA | NA | NA | NA | 1528 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Agata Records | NA | NA | NA | NA | 17388 | NA | NA | NA | FALSE | FALSE | FALSE |
| Song | Ancestral Echoes | TRUE | 1991 | Dream Pop | FALSE | 11793 | NA | NA | NA | FALSE | FALSE | FALSE |
| Song | Ancestral Echoes | FALSE | 2039 | Avant-Garde Folk | TRUE | 17133 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Angela Thompson | NA | NA | NA | NA | 1150 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Angela Thompson | NA | NA | NA | NA | 13448 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Anthony Davis | NA | NA | NA | NA | 8692 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Anthony Davis | NA | NA | NA | NA | 12452 | NA | Astral Concord | NA | FALSE | FALSE | FALSE |
| Person | Anthony Smith | NA | NA | NA | NA | 5719 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Anthony Smith | NA | NA | NA | NA | 7694 | NA | Electric Runaway | NA | FALSE | FALSE | FALSE |
| Person | Asuka Takahashi | NA | NA | NA | NA | 56 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Asuka Takahashi | NA | NA | NA | NA | 13588 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Asuka Takahashi | NA | NA | NA | NA | 15083 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Brandon Wilson | NA | NA | NA | NA | 10951 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Brandon Wilson | NA | NA | NA | NA | 13788 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Brian Gonzalez | NA | NA | NA | NA | 5974 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Brian Gonzalez | NA | NA | NA | NA | 10770 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Bryan Garcia | NA | NA | NA | NA | 9235 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Bryan Garcia | NA | NA | NA | NA | 10917 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Bryan Smith | NA | NA | NA | NA | 1638 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Bryan Smith | NA | NA | NA | NA | 9633 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Bryan Smith | NA | NA | NA | NA | 15404 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Calende Sound | NA | NA | NA | NA | 69 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Calende Sound | NA | NA | NA | NA | 17371 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Center Sound | NA | NA | NA | NA | 979 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Center Sound | NA | NA | NA | NA | 17380 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Bai | NA | NA | NA | NA | 227 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Bai | NA | NA | NA | NA | 7070 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Bai | NA | NA | NA | NA | 8092 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Bai | NA | NA | NA | NA | 10719 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cai | NA | NA | NA | NA | 5353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cai | NA | NA | NA | NA | 9395 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cao | NA | NA | NA | NA | 6082 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cao | NA | NA | NA | NA | 11458 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Chang | NA | NA | NA | NA | 3790 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Chang | NA | NA | NA | NA | 6874 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Chang | NA | NA | NA | NA | 7400 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Chen | NA | NA | NA | NA | 5544 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Chen | NA | NA | NA | NA | 8183 | NA | Andy Storm | NA | FALSE | FALSE | FALSE |
| Person | Chao Chen | NA | NA | NA | NA | 14121 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cheng | NA | NA | NA | NA | 12904 | NA | XPLICIT KAI | NA | FALSE | FALSE | FALSE |
| Person | Chao Cheng | NA | NA | NA | NA | 12927 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cheng | NA | NA | NA | NA | 13052 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cui | NA | NA | NA | NA | 4807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cui | NA | NA | NA | NA | 10254 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Cui | NA | NA | NA | NA | 13785 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Dai | NA | NA | NA | NA | 4054 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Dai | NA | NA | NA | NA | 7145 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Dai | NA | NA | NA | NA | 10964 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Dai | NA | NA | NA | NA | 11594 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Ding | NA | NA | NA | NA | 7840 | NA | Maya Star | NA | FALSE | FALSE | FALSE |
| Person | Chao Ding | NA | NA | NA | NA | 8380 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Ding | NA | NA | NA | NA | 15257 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Dong | NA | NA | NA | NA | 12108 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Dong | NA | NA | NA | NA | 13003 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Duan | NA | NA | NA | NA | 2376 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Duan | NA | NA | NA | NA | 6090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Fan | NA | NA | NA | NA | 3585 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Fan | NA | NA | NA | NA | 6207 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Fan | NA | NA | NA | NA | 11025 | NA | WXLF | NA | FALSE | FALSE | FALSE |
| Person | Chao Fan | NA | NA | NA | NA | 11505 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Fan | NA | NA | NA | NA | 14959 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Fan | NA | NA | NA | NA | 16467 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Fang | NA | NA | NA | NA | 2941 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Fang | NA | NA | NA | NA | 5423 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Fang | NA | NA | NA | NA | 9093 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Gao | NA | NA | NA | NA | 2261 | NA | Solar Arcadia | NA | FALSE | FALSE | FALSE |
| Person | Chao Gao | NA | NA | NA | NA | 2564 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Gao | NA | NA | NA | NA | 7167 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Gong | NA | NA | NA | NA | 6185 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Gong | NA | NA | NA | NA | 11057 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Guo | NA | NA | NA | NA | 1624 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Guo | NA | NA | NA | NA | 7795 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Guo | NA | NA | NA | NA | 11163 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Han | NA | NA | NA | NA | 1712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Han | NA | NA | NA | NA | 9484 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Han | NA | NA | NA | NA | 14888 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Han | NA | NA | NA | NA | 15203 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Hou | NA | NA | NA | NA | 4990 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Hou | NA | NA | NA | NA | 8909 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jia | NA | NA | NA | NA | 3701 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jia | NA | NA | NA | NA | 9880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jia | NA | NA | NA | NA | 15588 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jiang | NA | NA | NA | NA | 2881 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jiang | NA | NA | NA | NA | 6440 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jiang | NA | NA | NA | NA | 8031 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jin | NA | NA | NA | NA | 500 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jin | NA | NA | NA | NA | 7922 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Jin | NA | NA | NA | NA | 11894 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Kong | NA | NA | NA | NA | 1058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Kong | NA | NA | NA | NA | 7742 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Kong | NA | NA | NA | NA | 13482 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Lai | NA | NA | NA | NA | 11040 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Lai | NA | NA | NA | NA | 13882 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Li | NA | NA | NA | NA | 2634 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Li | NA | NA | NA | NA | 7338 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Li | NA | NA | NA | NA | 15091 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Liang | NA | NA | NA | NA | 14597 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Liang | NA | NA | NA | NA | 16712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Liao | NA | NA | NA | NA | 5399 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Liao | NA | NA | NA | NA | 14280 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Lin | NA | NA | NA | NA | 6822 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Lin | NA | NA | NA | NA | 13770 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Liu | NA | NA | NA | NA | 13510 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Liu | NA | NA | NA | NA | 15798 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Luo | NA | NA | NA | NA | 4711 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Luo | NA | NA | NA | NA | 12697 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Mao | NA | NA | NA | NA | 6353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Mao | NA | NA | NA | NA | 16165 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Peng | NA | NA | NA | NA | 6492 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Peng | NA | NA | NA | NA | 7270 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Peng | NA | NA | NA | NA | 8117 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Peng | NA | NA | NA | NA | 8768 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Peng | NA | NA | NA | NA | 16112 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qian | NA | NA | NA | NA | 1523 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qian | NA | NA | NA | NA | 7809 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qian | NA | NA | NA | NA | 14391 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qian | NA | NA | NA | NA | 14595 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qiao | NA | NA | NA | NA | 171 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qiao | NA | NA | NA | NA | 6490 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qiao | NA | NA | NA | NA | 8884 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qin | NA | NA | NA | NA | 2636 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qin | NA | NA | NA | NA | 15739 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qiu | NA | NA | NA | NA | 820 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qiu | NA | NA | NA | NA | 1086 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qiu | NA | NA | NA | NA | 9495 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qiu | NA | NA | NA | NA | 14071 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Qiu | NA | NA | NA | NA | 15418 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Ren | NA | NA | NA | NA | 12253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Ren | NA | NA | NA | NA | 12725 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Shao | NA | NA | NA | NA | 10810 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Shao | NA | NA | NA | NA | 13261 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Shen | NA | NA | NA | NA | 493 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Shen | NA | NA | NA | NA | 8415 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Shen | NA | NA | NA | NA | 11846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Shi | NA | NA | NA | NA | 6222 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Shi | NA | NA | NA | NA | 10762 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Song | NA | NA | NA | NA | 3543 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Song | NA | NA | NA | NA | 6277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Song | NA | NA | NA | NA | 12388 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tang | NA | NA | NA | NA | 3831 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tang | NA | NA | NA | NA | 11324 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tao | NA | NA | NA | NA | 11350 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tao | NA | NA | NA | NA | 13571 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tian | NA | NA | NA | NA | 1137 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tian | NA | NA | NA | NA | 2571 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tian | NA | NA | NA | NA | 6803 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tian | NA | NA | NA | NA | 8783 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tian | NA | NA | NA | NA | 11784 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Tian | NA | NA | NA | NA | 16059 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wan | NA | NA | NA | NA | 1802 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wan | NA | NA | NA | NA | 4079 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wan | NA | NA | NA | NA | 6450 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wan | NA | NA | NA | NA | 16463 | NA | The Lost Vanguard | NA | FALSE | FALSE | FALSE |
| Person | Chao Wang | NA | NA | NA | NA | 4326 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wang | NA | NA | NA | NA | 10038 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wang | NA | NA | NA | NA | 16469 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wei | NA | NA | NA | NA | 9752 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wei | NA | NA | NA | NA | 12474 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wei | NA | NA | NA | NA | 12785 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 2156 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 2312 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 3030 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 4970 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 6448 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 7049 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 9075 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 9222 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Wu | NA | NA | NA | NA | 15064 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xiang | NA | NA | NA | NA | 12737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xiang | NA | NA | NA | NA | 12962 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xiao | NA | NA | NA | NA | 3714 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xiao | NA | NA | NA | NA | 7606 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xiao | NA | NA | NA | NA | 13432 | NA | FLEX ALPHA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xie | NA | NA | NA | NA | 12612 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xie | NA | NA | NA | NA | 13722 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xiong | NA | NA | NA | NA | 8120 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xiong | NA | NA | NA | NA | 9027 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xiong | NA | NA | NA | NA | 12304 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xu | NA | NA | NA | NA | 4802 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xu | NA | NA | NA | NA | 6014 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xu | NA | NA | NA | NA | 6956 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xu | NA | NA | NA | NA | 10047 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xue | NA | NA | NA | NA | 10144 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Xue | NA | NA | NA | NA | 15504 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yan | NA | NA | NA | NA | 2231 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yan | NA | NA | NA | NA | 4184 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yan | NA | NA | NA | NA | 9167 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yan | NA | NA | NA | NA | 10278 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yang | NA | NA | NA | NA | 539 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yang | NA | NA | NA | NA | 1314 | NA | Neon Moth | NA | FALSE | FALSE | FALSE |
| Person | Chao Yang | NA | NA | NA | NA | 6516 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yang | NA | NA | NA | NA | 16331 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yao | NA | NA | NA | NA | 967 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yao | NA | NA | NA | NA | 4234 | NA | The Lunar Manifesto | NA | FALSE | FALSE | FALSE |
| Person | Chao Yao | NA | NA | NA | NA | 6546 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yao | NA | NA | NA | NA | 6975 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yao | NA | NA | NA | NA | 15887 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Ye | NA | NA | NA | NA | 5210 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Ye | NA | NA | NA | NA | 9257 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yi | NA | NA | NA | NA | 5809 | NA | PHVNTOM | NA | FALSE | FALSE | FALSE |
| Person | Chao Yi | NA | NA | NA | NA | 8125 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yi | NA | NA | NA | NA | 10416 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yi | NA | NA | NA | NA | 10422 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yi | NA | NA | NA | NA | 10604 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yi | NA | NA | NA | NA | 13899 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yu | NA | NA | NA | NA | 170 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yu | NA | NA | NA | NA | 5494 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yu | NA | NA | NA | NA | 13293 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yuan | NA | NA | NA | NA | 7427 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yuan | NA | NA | NA | NA | 11871 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yuan | NA | NA | NA | NA | 13983 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Yuan | NA | NA | NA | NA | 14043 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zeng | NA | NA | NA | NA | 2325 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zeng | NA | NA | NA | NA | 12151 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhang | NA | NA | NA | NA | 12851 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhang | NA | NA | NA | NA | 15918 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhao | NA | NA | NA | NA | 9103 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhao | NA | NA | NA | NA | 10005 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhao | NA | NA | NA | NA | 11171 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhao | NA | NA | NA | NA | 13599 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhao | NA | NA | NA | NA | 15519 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhao | NA | NA | NA | NA | 16595 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhong | NA | NA | NA | NA | 6779 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhong | NA | NA | NA | NA | 10219 | NA | Dawn | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhong | NA | NA | NA | NA | 12730 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhong | NA | NA | NA | NA | 13210 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhong | NA | NA | NA | NA | 15915 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhou | NA | NA | NA | NA | 7820 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhou | NA | NA | NA | NA | 16278 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhu | NA | NA | NA | NA | 935 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhu | NA | NA | NA | NA | 7069 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhu | NA | NA | NA | NA | 10485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhu | NA | NA | NA | NA | 11460 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Chao Zhu | NA | NA | NA | NA | 16388 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Charles Jacobs | NA | NA | NA | NA | 5621 | NA | BIGG STACCZ | NA | FALSE | FALSE | FALSE |
| Person | Charles Jacobs | NA | NA | NA | NA | 5754 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christine Jones | NA | NA | NA | NA | 4692 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christine Jones | NA | NA | NA | NA | 7528 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christine Jones | NA | NA | NA | NA | 8337 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Davis | NA | NA | NA | NA | 5989 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Davis | NA | NA | NA | NA | 15768 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Hill | NA | NA | NA | NA | 12643 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Hill | NA | NA | NA | NA | 14257 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Johnson | NA | NA | NA | NA | 8443 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Johnson | NA | NA | NA | NA | 8532 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Smith | NA | NA | NA | NA | 2660 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Smith | NA | NA | NA | NA | 3038 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Christopher Smith | NA | NA | NA | NA | 15510 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Coastal Echoes | NA | NA | NA | NA | 4022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Album | Coastal Echoes | NA | 2023 | Psychedelic Rock | TRUE | 15065 | 2019 | NA | 2039 | FALSE | FALSE | FALSE |
| RecordLabel | Coastal Harmony Studios | NA | NA | NA | NA | 1394 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Coastal Harmony Studios | NA | NA | NA | NA | 17369 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Cultural Harmony | NA | NA | NA | NA | 1599 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Cultural Harmony | NA | NA | NA | NA | 17390 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Daniel Johnson | NA | NA | NA | NA | 4266 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Daniel Johnson | NA | NA | NA | NA | 10458 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Armstrong | NA | NA | NA | NA | 4878 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Armstrong | NA | NA | NA | NA | 8191 | NA | Celestial Anomaly | NA | FALSE | FALSE | FALSE |
| Person | David Flores | NA | NA | NA | NA | 14050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Flores | NA | NA | NA | NA | 15039 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Jenkins | NA | NA | NA | NA | 5143 | NA | The Lotus | NA | FALSE | FALSE | FALSE |
| Person | David Jenkins | NA | NA | NA | NA | 11731 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Johnson | NA | NA | NA | NA | 1036 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Johnson | NA | NA | NA | NA | 7666 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Moore | NA | NA | NA | NA | 4198 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Moore | NA | NA | NA | NA | 10696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Williams | NA | NA | NA | NA | 793 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | David Williams | NA | NA | NA | NA | 2688 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Denise Bell | NA | NA | NA | NA | 415 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Denise Bell | NA | NA | NA | NA | 2358 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Donna Ryan | NA | NA | NA | NA | 1827 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Donna Ryan | NA | NA | NA | NA | 8353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Dwayne Wilson | NA | NA | NA | NA | 4134 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Dwayne Wilson | NA | NA | NA | NA | 5922 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Elizabeth Chase | NA | NA | NA | NA | 898 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Elizabeth Chase | NA | NA | NA | NA | 12077 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Elizabeth Gonzalez | NA | NA | NA | NA | 6129 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Elizabeth Gonzalez | NA | NA | NA | NA | 15134 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Elizabeth Johnson | NA | NA | NA | NA | 990 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Elizabeth Johnson | NA | NA | NA | NA | 15467 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Emily Taylor | NA | NA | NA | NA | 8974 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Emily Taylor | NA | NA | NA | NA | 10445 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Chang | NA | NA | NA | NA | 9034 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Chang | NA | NA | NA | NA | 9589 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Chen | NA | NA | NA | NA | 696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Chen | NA | NA | NA | NA | 4173 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Chen | NA | NA | NA | NA | 13292 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Cui | NA | NA | NA | NA | 975 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Cui | NA | NA | NA | NA | 7214 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Cui | NA | NA | NA | NA | 16105 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Dai | NA | NA | NA | NA | 6840 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Dai | NA | NA | NA | NA | 13022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Dai | NA | NA | NA | NA | 14423 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Deng | NA | NA | NA | NA | 1092 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Deng | NA | NA | NA | NA | 13566 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ding | NA | NA | NA | NA | 4346 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ding | NA | NA | NA | NA | 9417 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ding | NA | NA | NA | NA | 14895 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Dong | NA | NA | NA | NA | 4423 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Dong | NA | NA | NA | NA | 6381 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Dong | NA | NA | NA | NA | 15008 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Du | NA | NA | NA | NA | 1590 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Du | NA | NA | NA | NA | 2133 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Du | NA | NA | NA | NA | 13513 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Du | NA | NA | NA | NA | 13619 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Du | NA | NA | NA | NA | 16130 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Duan | NA | NA | NA | NA | 3712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Duan | NA | NA | NA | NA | 6086 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Duan | NA | NA | NA | NA | 8304 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Feng | NA | NA | NA | NA | 8826 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Feng | NA | NA | NA | NA | 9452 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Feng | NA | NA | NA | NA | 12327 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Feng | NA | NA | NA | NA | 13420 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Fu | NA | NA | NA | NA | 2382 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Fu | NA | NA | NA | NA | 15620 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Gao | NA | NA | NA | NA | 1363 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Gao | NA | NA | NA | NA | 7274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Gao | NA | NA | NA | NA | 9591 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Gao | NA | NA | NA | NA | 13739 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Gu | NA | NA | NA | NA | 3439 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Gu | NA | NA | NA | NA | 5104 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Gu | NA | NA | NA | NA | 7058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Gu | NA | NA | NA | NA | 8921 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Han | NA | NA | NA | NA | 3736 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Han | NA | NA | NA | NA | 6453 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Han | NA | NA | NA | NA | 13897 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Hao | NA | NA | NA | NA | 856 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Hao | NA | NA | NA | NA | 6336 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang He | NA | NA | NA | NA | 2236 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang He | NA | NA | NA | NA | 12387 | NA | Requiem | NA | FALSE | FALSE | FALSE |
| Person | Fang Hou | NA | NA | NA | NA | 7075 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Hou | NA | NA | NA | NA | 15549 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Hu | NA | NA | NA | NA | 6789 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Hu | NA | NA | NA | NA | 13192 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Jiang | NA | NA | NA | NA | 1769 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Jiang | NA | NA | NA | NA | 12646 | NA | Fang | NA | FALSE | FALSE | FALSE |
| Person | Fang Kong | NA | NA | NA | NA | 136 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Kong | NA | NA | NA | NA | 2892 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Kong | NA | NA | NA | NA | 3268 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Kong | NA | NA | NA | NA | 5008 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Kong | NA | NA | NA | NA | 5947 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lai | NA | NA | NA | NA | 2263 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lai | NA | NA | NA | NA | 16051 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lei | NA | NA | NA | NA | 10463 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lei | NA | NA | NA | NA | 12763 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Liang | NA | NA | NA | NA | 1270 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Liang | NA | NA | NA | NA | 1409 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Liang | NA | NA | NA | NA | 15393 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Liang | NA | NA | NA | NA | 16549 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lin | NA | NA | NA | NA | 3474 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lin | NA | NA | NA | NA | 4808 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lin | NA | NA | NA | NA | 5033 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lin | NA | NA | NA | NA | 14906 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Liu | NA | NA | NA | NA | 3641 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Liu | NA | NA | NA | NA | 9939 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Liu | NA | NA | NA | NA | 11759 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lu | NA | NA | NA | NA | 5502 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lu | NA | NA | NA | NA | 9028 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Lu | NA | NA | NA | NA | 12377 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Luo | NA | NA | NA | NA | 3973 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Luo | NA | NA | NA | NA | 16358 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ma | NA | NA | NA | NA | 7930 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ma | NA | NA | NA | NA | 10466 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ma | NA | NA | NA | NA | 12192 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ma | NA | NA | NA | NA | 15466 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Mao | NA | NA | NA | NA | 3045 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Mao | NA | NA | NA | NA | 10251 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Mao | NA | NA | NA | NA | 15921 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Mao | NA | NA | NA | NA | 16685 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Meng | NA | NA | NA | NA | 3812 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Meng | NA | NA | NA | NA | 4798 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Meng | NA | NA | NA | NA | 10473 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Mo | NA | NA | NA | NA | 2178 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Mo | NA | NA | NA | NA | 6249 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Pan | NA | NA | NA | NA | 1428 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Pan | NA | NA | NA | NA | 10263 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Pan | NA | NA | NA | NA | 11086 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Pan | NA | NA | NA | NA | 13084 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qian | NA | NA | NA | NA | 3211 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qian | NA | NA | NA | NA | 11754 | NA | Solar Fang | NA | FALSE | FALSE | FALSE |
| Person | Fang Qian | NA | NA | NA | NA | 11953 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qian | NA | NA | NA | NA | 14839 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qiao | NA | NA | NA | NA | 9318 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qiao | NA | NA | NA | NA | 13176 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qiao | NA | NA | NA | NA | 16532 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qin | NA | NA | NA | NA | 7675 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qin | NA | NA | NA | NA | 8645 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qiu | NA | NA | NA | NA | 8827 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Qiu | NA | NA | NA | NA | 15733 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ren | NA | NA | NA | NA | 4035 | NA | Aria Snow | NA | FALSE | FALSE | FALSE |
| Person | Fang Ren | NA | NA | NA | NA | 10496 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ren | NA | NA | NA | NA | 14176 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Ren | NA | NA | NA | NA | 14539 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Shen | NA | NA | NA | NA | 1801 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Shen | NA | NA | NA | NA | 10824 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Shen | NA | NA | NA | NA | 12335 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Shen | NA | NA | NA | NA | 15888 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Shi | NA | NA | NA | NA | 5439 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Shi | NA | NA | NA | NA | 8071 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Su | NA | NA | NA | NA | 1241 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Su | NA | NA | NA | NA | 2991 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Su | NA | NA | NA | NA | 8777 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Su | NA | NA | NA | NA | 15124 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tan | NA | NA | NA | NA | 6037 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tan | NA | NA | NA | NA | 12649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tang | NA | NA | NA | NA | 1386 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tang | NA | NA | NA | NA | 6522 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tang | NA | NA | NA | NA | 6719 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tang | NA | NA | NA | NA | 11134 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tao | NA | NA | NA | NA | 1644 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tao | NA | NA | NA | NA | 1764 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tao | NA | NA | NA | NA | 3262 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tao | NA | NA | NA | NA | 4759 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tao | NA | NA | NA | NA | 12700 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tao | NA | NA | NA | NA | 15283 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tian | NA | NA | NA | NA | 8319 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Tian | NA | NA | NA | NA | 11587 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wan | NA | NA | NA | NA | 494 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wan | NA | NA | NA | NA | 13160 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wan | NA | NA | NA | NA | 16022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wei | NA | NA | NA | NA | 7841 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wei | NA | NA | NA | NA | 8160 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wei | NA | NA | NA | NA | 9154 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wei | NA | NA | NA | NA | 13428 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wei | NA | NA | NA | NA | 15284 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wu | NA | NA | NA | NA | 685 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wu | NA | NA | NA | NA | 13090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Wu | NA | NA | NA | NA | 14713 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xia | NA | NA | NA | NA | 1551 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xia | NA | NA | NA | NA | 7719 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xiang | NA | NA | NA | NA | 6312 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xiang | NA | NA | NA | NA | 8979 | NA | THVNDER | NA | FALSE | FALSE | FALSE |
| Person | Fang Xiang | NA | NA | NA | NA | 10095 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xiao | NA | NA | NA | NA | 5208 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xiao | NA | NA | NA | NA | 12303 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xiao | NA | NA | NA | NA | 12480 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xie | NA | NA | NA | NA | 1870 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xie | NA | NA | NA | NA | 8824 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xiong | NA | NA | NA | NA | 2377 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xiong | NA | NA | NA | NA | 5781 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xu | NA | NA | NA | NA | 1591 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Xu | NA | NA | NA | NA | 16506 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yan | NA | NA | NA | NA | 4048 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yan | NA | NA | NA | NA | 14694 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yan | NA | NA | NA | NA | 15019 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yao | NA | NA | NA | NA | 6219 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yao | NA | NA | NA | NA | 14772 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yi | NA | NA | NA | NA | 2264 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yi | NA | NA | NA | NA | 9881 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yi | NA | NA | NA | NA | 12255 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yi | NA | NA | NA | NA | 14022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yin | NA | NA | NA | NA | 5342 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yin | NA | NA | NA | NA | 6039 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yin | NA | NA | NA | NA | 9510 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yin | NA | NA | NA | NA | 15177 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yu | NA | NA | NA | NA | 2103 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yu | NA | NA | NA | NA | 13744 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yuan | NA | NA | NA | NA | 2015 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Yuan | NA | NA | NA | NA | 2531 | NA | Jordan Miles | NA | FALSE | FALSE | FALSE |
| Person | Fang Yuan | NA | NA | NA | NA | 16681 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zheng | NA | NA | NA | NA | 2764 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zheng | NA | NA | NA | NA | 3277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zheng | NA | NA | NA | NA | 9215 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zheng | NA | NA | NA | NA | 11059 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhong | NA | NA | NA | NA | 113 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhong | NA | NA | NA | NA | 936 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhong | NA | NA | NA | NA | 6176 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhou | NA | NA | NA | NA | 2758 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhou | NA | NA | NA | NA | 4601 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhou | NA | NA | NA | NA | 9066 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhou | NA | NA | NA | NA | 16573 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhu | NA | NA | NA | NA | 3462 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zhu | NA | NA | NA | NA | 9507 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zou | NA | NA | NA | NA | 201 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zou | NA | NA | NA | NA | 439 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zou | NA | NA | NA | NA | 1327 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zou | NA | NA | NA | NA | 9046 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Fang Zou | NA | NA | NA | NA | 15800 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Freefall Music | NA | NA | NA | NA | 290 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Freefall Music | NA | NA | NA | NA | 17374 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Bai | NA | NA | NA | NA | 317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Bai | NA | NA | NA | NA | 2840 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Bai | NA | NA | NA | NA | 10524 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Bai | NA | NA | NA | NA | 16446 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Bai | NA | NA | NA | NA | 16578 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Cai | NA | NA | NA | NA | 5849 | NA | Zane Ellis | NA | FALSE | FALSE | FALSE |
| Person | Gang Cai | NA | NA | NA | NA | 10942 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Cai | NA | NA | NA | NA | 12699 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Cao | NA | NA | NA | NA | 1248 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Cao | NA | NA | NA | NA | 15176 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Cao | NA | NA | NA | NA | 15613 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Chen | NA | NA | NA | NA | 361 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Chen | NA | NA | NA | NA | 687 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Chen | NA | NA | NA | NA | 7637 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Chen | NA | NA | NA | NA | 8033 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Chen | NA | NA | NA | NA | 10588 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Chen | NA | NA | NA | NA | 10896 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Chen | NA | NA | NA | NA | 12747 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Chen | NA | NA | NA | NA | 16170 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Cui | NA | NA | NA | NA | 440 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Cui | NA | NA | NA | NA | 9315 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Cui | NA | NA | NA | NA | 9755 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Dai | NA | NA | NA | NA | 6572 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Dai | NA | NA | NA | NA | 13593 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Deng | NA | NA | NA | NA | 2642 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Deng | NA | NA | NA | NA | 4485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Dong | NA | NA | NA | NA | 3365 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Dong | NA | NA | NA | NA | 8501 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Dong | NA | NA | NA | NA | 12845 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Dong | NA | NA | NA | NA | 13377 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Du | NA | NA | NA | NA | 1345 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Du | NA | NA | NA | NA | 5269 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Du | NA | NA | NA | NA | 8067 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Du | NA | NA | NA | NA | 15999 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Duan | NA | NA | NA | NA | 3738 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Duan | NA | NA | NA | NA | 4739 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Duan | NA | NA | NA | NA | 16701 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fan | NA | NA | NA | NA | 4984 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fan | NA | NA | NA | NA | 6274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fan | NA | NA | NA | NA | 10846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fan | NA | NA | NA | NA | 13944 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fan | NA | NA | NA | NA | 14471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fan | NA | NA | NA | NA | 15354 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fu | NA | NA | NA | NA | 7690 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fu | NA | NA | NA | NA | 12296 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Fu | NA | NA | NA | NA | 12299 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Gao | NA | NA | NA | NA | 9313 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Gao | NA | NA | NA | NA | 10042 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Han | NA | NA | NA | NA | 2235 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Han | NA | NA | NA | NA | 7638 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Hao | NA | NA | NA | NA | 3679 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Hao | NA | NA | NA | NA | 8685 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang He | NA | NA | NA | NA | 5581 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang He | NA | NA | NA | NA | 10675 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang He | NA | NA | NA | NA | 10780 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang He | NA | NA | NA | NA | 10829 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang He | NA | NA | NA | NA | 12064 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang He | NA | NA | NA | NA | 13170 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang He | NA | NA | NA | NA | 15664 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Hu | NA | NA | NA | NA | 3024 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Hu | NA | NA | NA | NA | 4290 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Huang | NA | NA | NA | NA | 3880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Huang | NA | NA | NA | NA | 5090 | NA | Dante Cruz | NA | FALSE | FALSE | FALSE |
| Person | Gang Jia | NA | NA | NA | NA | 1181 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Jia | NA | NA | NA | NA | 5493 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Jia | NA | NA | NA | NA | 6026 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Jia | NA | NA | NA | NA | 8627 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Jia | NA | NA | NA | NA | 15916 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Jiang | NA | NA | NA | NA | 2663 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Jiang | NA | NA | NA | NA | 4796 | NA | Cosmic Noir | NA | FALSE | FALSE | FALSE |
| Person | Gang Kong | NA | NA | NA | NA | 11600 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Kong | NA | NA | NA | NA | 15939 | NA | FVRE | NA | FALSE | FALSE | FALSE |
| Person | Gang Lai | NA | NA | NA | NA | 3247 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Lai | NA | NA | NA | NA | 14972 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Lei | NA | NA | NA | NA | 451 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Lei | NA | NA | NA | NA | 10486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Lei | NA | NA | NA | NA | 12548 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Liao | NA | NA | NA | NA | 650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Liao | NA | NA | NA | NA | 11416 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Lin | NA | NA | NA | NA | 13234 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Lin | NA | NA | NA | NA | 15940 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Long | NA | NA | NA | NA | 11 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Long | NA | NA | NA | NA | 15234 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Mao | NA | NA | NA | NA | 4211 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Mao | NA | NA | NA | NA | 7586 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Mao | NA | NA | NA | NA | 9846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Mao | NA | NA | NA | NA | 11954 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Pan | NA | NA | NA | NA | 1666 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Pan | NA | NA | NA | NA | 1851 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Pan | NA | NA | NA | NA | 5833 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Peng | NA | NA | NA | NA | 4137 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Peng | NA | NA | NA | NA | 4730 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Peng | NA | NA | NA | NA | 4787 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Peng | NA | NA | NA | NA | 13165 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qian | NA | NA | NA | NA | 3120 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qian | NA | NA | NA | NA | 5941 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qian | NA | NA | NA | NA | 15355 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qiao | NA | NA | NA | NA | 9152 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qiao | NA | NA | NA | NA | 14915 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qin | NA | NA | NA | NA | 2968 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qin | NA | NA | NA | NA | 3495 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qin | NA | NA | NA | NA | 6950 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Qin | NA | NA | NA | NA | 7257 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Ren | NA | NA | NA | NA | 5505 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Ren | NA | NA | NA | NA | 15297 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Shao | NA | NA | NA | NA | 888 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Shao | NA | NA | NA | NA | 3761 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Shao | NA | NA | NA | NA | 5780 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Shao | NA | NA | NA | NA | 8121 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Shen | NA | NA | NA | NA | 1275 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Shen | NA | NA | NA | NA | 11800 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Shen | NA | NA | NA | NA | 16103 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Su | NA | NA | NA | NA | 66 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Su | NA | NA | NA | NA | 926 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Sun | NA | NA | NA | NA | 3690 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Sun | NA | NA | NA | NA | 10216 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Sun | NA | NA | NA | NA | 12724 | NA | Ivory Hawk | NA | FALSE | FALSE | FALSE |
| Person | Gang Tan | NA | NA | NA | NA | 1711 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tan | NA | NA | NA | NA | 3529 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tan | NA | NA | NA | NA | 7002 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tan | NA | NA | NA | NA | 13048 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tang | NA | NA | NA | NA | 3044 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tang | NA | NA | NA | NA | 6886 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tang | NA | NA | NA | NA | 16314 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tian | NA | NA | NA | NA | 8455 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tian | NA | NA | NA | NA | 13121 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Tian | NA | NA | NA | NA | 13166 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Wan | NA | NA | NA | NA | 4545 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Wan | NA | NA | NA | NA | 8181 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Wan | NA | NA | NA | NA | 13586 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Wen | NA | NA | NA | NA | 1273 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Wen | NA | NA | NA | NA | 2504 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Wen | NA | NA | NA | NA | 11609 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Wen | NA | NA | NA | NA | 11709 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xia | NA | NA | NA | NA | 6005 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xia | NA | NA | NA | NA | 10104 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xia | NA | NA | NA | NA | 11803 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xiang | NA | NA | NA | NA | 2180 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xiang | NA | NA | NA | NA | 6739 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xiang | NA | NA | NA | NA | 9438 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xie | NA | NA | NA | NA | 7494 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xie | NA | NA | NA | NA | 7934 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xie | NA | NA | NA | NA | 8016 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Xie | NA | NA | NA | NA | 12735 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yang | NA | NA | NA | NA | 180 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yang | NA | NA | NA | NA | 5848 | NA | MNTL X (Mental X) | NA | FALSE | FALSE | FALSE |
| Person | Gang Yang | NA | NA | NA | NA | 7895 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yang | NA | NA | NA | NA | 12070 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yang | NA | NA | NA | NA | 14648 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yao | NA | NA | NA | NA | 11570 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yao | NA | NA | NA | NA | 16142 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Ye | NA | NA | NA | NA | 1299 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Ye | NA | NA | NA | NA | 14831 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Ye | NA | NA | NA | NA | 14930 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Ye | NA | NA | NA | NA | 16472 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yi | NA | NA | NA | NA | 10244 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yi | NA | NA | NA | NA | 15953 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yin | NA | NA | NA | NA | 1223 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yin | NA | NA | NA | NA | 3832 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yin | NA | NA | NA | NA | 9102 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yu | NA | NA | NA | NA | 5580 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yu | NA | NA | NA | NA | 6662 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yu | NA | NA | NA | NA | 6800 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yu | NA | NA | NA | NA | 7996 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yu | NA | NA | NA | NA | 8145 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yuan | NA | NA | NA | NA | 3233 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yuan | NA | NA | NA | NA | 9392 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Yuan | NA | NA | NA | NA | 9725 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zeng | NA | NA | NA | NA | 4989 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zeng | NA | NA | NA | NA | 6288 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zeng | NA | NA | NA | NA | 15647 | NA | Nightshade Paradox | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhang | NA | NA | NA | NA | 2603 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhang | NA | NA | NA | NA | 3834 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhang | NA | NA | NA | NA | 9408 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhao | NA | NA | NA | NA | 151 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhao | NA | NA | NA | NA | 684 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhao | NA | NA | NA | NA | 4467 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhao | NA | NA | NA | NA | 8550 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhao | NA | NA | NA | NA | 10966 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zheng | NA | NA | NA | NA | 2217 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zheng | NA | NA | NA | NA | 3691 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zheng | NA | NA | NA | NA | 10577 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhou | NA | NA | NA | NA | 1071 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhou | NA | NA | NA | NA | 3914 | NA | The Element | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhou | NA | NA | NA | NA | 13111 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhou | NA | NA | NA | NA | 13612 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhu | NA | NA | NA | NA | 6944 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zhu | NA | NA | NA | NA | 12140 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zou | NA | NA | NA | NA | 11540 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Gang Zou | NA | NA | NA | NA | 14135 | NA | Lunar Confetti | NA | FALSE | FALSE | FALSE |
| Person | Gang Zou | NA | NA | NA | NA | 16316 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Bai | NA | NA | NA | NA | 1098 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Bai | NA | NA | NA | NA | 4121 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Bai | NA | NA | NA | NA | 11584 | NA | Echo Reverie | NA | FALSE | FALSE | FALSE |
| Person | Guiying Bai | NA | NA | NA | NA | 11973 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Bai | NA | NA | NA | NA | 14793 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Chang | NA | NA | NA | NA | 8625 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Chang | NA | NA | NA | NA | 12370 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Chang | NA | NA | NA | NA | 13829 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Chen | NA | NA | NA | NA | 3380 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Chen | NA | NA | NA | NA | 14196 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Cui | NA | NA | NA | NA | 3440 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Cui | NA | NA | NA | NA | 6531 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Dai | NA | NA | NA | NA | 3197 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Dai | NA | NA | NA | NA | 10161 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Dai | NA | NA | NA | NA | 10912 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Deng | NA | NA | NA | NA | 6784 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Deng | NA | NA | NA | NA | 13981 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ding | NA | NA | NA | NA | 1337 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ding | NA | NA | NA | NA | 8741 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ding | NA | NA | NA | NA | 15906 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Dong | NA | NA | NA | NA | 7591 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Dong | NA | NA | NA | NA | 8123 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Dong | NA | NA | NA | NA | 16731 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Duan | NA | NA | NA | NA | 1210 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Duan | NA | NA | NA | NA | 4552 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Fan | NA | NA | NA | NA | 8460 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Fan | NA | NA | NA | NA | 11912 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Fan | NA | NA | NA | NA | 14445 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Fang | NA | NA | NA | NA | 352 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Fang | NA | NA | NA | NA | 11686 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Feng | NA | NA | NA | NA | 183 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Feng | NA | NA | NA | NA | 14924 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Fu | NA | NA | NA | NA | 5397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Fu | NA | NA | NA | NA | 12969 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Fu | NA | NA | NA | NA | 14209 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gao | NA | NA | NA | NA | 2978 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gao | NA | NA | NA | NA | 4032 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gao | NA | NA | NA | NA | 14193 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gong | NA | NA | NA | NA | 3319 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gong | NA | NA | NA | NA | 11918 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gong | NA | NA | NA | NA | 16140 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gu | NA | NA | NA | NA | 638 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gu | NA | NA | NA | NA | 8925 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Gu | NA | NA | NA | NA | 13217 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Han | NA | NA | NA | NA | 8939 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Han | NA | NA | NA | NA | 12760 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Hao | NA | NA | NA | NA | 9309 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Hao | NA | NA | NA | NA | 10560 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Hao | NA | NA | NA | NA | 12863 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying He | NA | NA | NA | NA | 8507 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying He | NA | NA | NA | NA | 13191 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying He | NA | NA | NA | NA | 13737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Hou | NA | NA | NA | NA | 5245 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Hou | NA | NA | NA | NA | 5266 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Hou | NA | NA | NA | NA | 5769 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Hou | NA | NA | NA | NA | 10910 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Huang | NA | NA | NA | NA | 6053 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Huang | NA | NA | NA | NA | 11757 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Jia | NA | NA | NA | NA | 5381 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Jia | NA | NA | NA | NA | 12731 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Jiang | NA | NA | NA | NA | 840 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Jiang | NA | NA | NA | NA | 1713 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Jiang | NA | NA | NA | NA | 8668 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Jin | NA | NA | NA | NA | 5441 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Jin | NA | NA | NA | NA | 9095 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Jin | NA | NA | NA | NA | 16633 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Kang | NA | NA | NA | NA | 6554 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Kang | NA | NA | NA | NA | 9809 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Kang | NA | NA | NA | NA | 11102 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Kang | NA | NA | NA | NA | 14624 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Kang | NA | NA | NA | NA | 14847 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Kong | NA | NA | NA | NA | 3997 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Kong | NA | NA | NA | NA | 16502 | NA | Blue Ashes | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lai | NA | NA | NA | NA | 3798 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lai | NA | NA | NA | NA | 15773 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lei | NA | NA | NA | NA | 7248 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lei | NA | NA | NA | NA | 10297 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lei | NA | NA | NA | NA | 10652 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lei | NA | NA | NA | NA | 11852 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Liang | NA | NA | NA | NA | 11597 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Liang | NA | NA | NA | NA | 15543 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Liao | NA | NA | NA | NA | 1180 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Liao | NA | NA | NA | NA | 4098 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Liao | NA | NA | NA | NA | 10920 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Liao | NA | NA | NA | NA | 14484 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lin | NA | NA | NA | NA | 4360 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lin | NA | NA | NA | NA | 6917 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lin | NA | NA | NA | NA | 11821 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lu | NA | NA | NA | NA | 1842 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lu | NA | NA | NA | NA | 5440 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Lu | NA | NA | NA | NA | 16654 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ma | NA | NA | NA | NA | 7588 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ma | NA | NA | NA | NA | 7716 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ma | NA | NA | NA | NA | 14200 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Meng | NA | NA | NA | NA | 9523 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Meng | NA | NA | NA | NA | 16598 | NA | Mia Stone | NA | FALSE | FALSE | FALSE |
| Person | Guiying Mo | NA | NA | NA | NA | 10725 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Mo | NA | NA | NA | NA | 11601 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Pan | NA | NA | NA | NA | 67 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Pan | NA | NA | NA | NA | 202 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Pan | NA | NA | NA | NA | 535 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Pan | NA | NA | NA | NA | 5627 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Pan | NA | NA | NA | NA | 10257 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Pan | NA | NA | NA | NA | 10407 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Peng | NA | NA | NA | NA | 2254 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Peng | NA | NA | NA | NA | 3930 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Peng | NA | NA | NA | NA | 11913 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Peng | NA | NA | NA | NA | 14560 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qian | NA | NA | NA | NA | 12432 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qian | NA | NA | NA | NA | 14186 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qiao | NA | NA | NA | NA | 7294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qiao | NA | NA | NA | NA | 10487 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qin | NA | NA | NA | NA | 51 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qin | NA | NA | NA | NA | 443 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qin | NA | NA | NA | NA | 6824 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qin | NA | NA | NA | NA | 7995 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qin | NA | NA | NA | NA | 13328 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qiu | NA | NA | NA | NA | 13178 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qiu | NA | NA | NA | NA | 13895 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Qiu | NA | NA | NA | NA | 16102 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ren | NA | NA | NA | NA | 2426 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ren | NA | NA | NA | NA | 2765 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ren | NA | NA | NA | NA | 5485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ren | NA | NA | NA | NA | 6475 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ren | NA | NA | NA | NA | 10906 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shao | NA | NA | NA | NA | 2710 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shao | NA | NA | NA | NA | 6980 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shao | NA | NA | NA | NA | 11691 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shao | NA | NA | NA | NA | 12080 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shao | NA | NA | NA | NA | 15560 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shen | NA | NA | NA | NA | 7806 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shen | NA | NA | NA | NA | 8671 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shen | NA | NA | NA | NA | 11433 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shen | NA | NA | NA | NA | 15342 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shi | NA | NA | NA | NA | 633 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shi | NA | NA | NA | NA | 3432 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shi | NA | NA | NA | NA | 8742 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shi | NA | NA | NA | NA | 10181 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shi | NA | NA | NA | NA | 13471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Shi | NA | NA | NA | NA | 15225 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Song | NA | NA | NA | NA | 10363 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Song | NA | NA | NA | NA | 12959 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Song | NA | NA | NA | NA | 13723 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Su | NA | NA | NA | NA | 2378 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Su | NA | NA | NA | NA | 4894 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Su | NA | NA | NA | NA | 14149 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tang | NA | NA | NA | NA | 11786 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tang | NA | NA | NA | NA | 11964 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tang | NA | NA | NA | NA | 15778 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tao | NA | NA | NA | NA | 4302 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tao | NA | NA | NA | NA | 6433 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tao | NA | NA | NA | NA | 14832 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tian | NA | NA | NA | NA | 1946 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tian | NA | NA | NA | NA | 3306 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tian | NA | NA | NA | NA | 11419 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Tian | NA | NA | NA | NA | 12160 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Wu | NA | NA | NA | NA | 3429 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Wu | NA | NA | NA | NA | 9784 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Xia | NA | NA | NA | NA | 3681 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Xia | NA | NA | NA | NA | 6969 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Xie | NA | NA | NA | NA | 2854 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Xie | NA | NA | NA | NA | 3297 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Xu | NA | NA | NA | NA | 6718 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Xu | NA | NA | NA | NA | 7168 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yan | NA | NA | NA | NA | 1410 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yan | NA | NA | NA | NA | 4741 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yang | NA | NA | NA | NA | 3974 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yang | NA | NA | NA | NA | 14838 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yao | NA | NA | NA | NA | 8320 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yao | NA | NA | NA | NA | 8700 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yao | NA | NA | NA | NA | 12537 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ye | NA | NA | NA | NA | 6449 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Ye | NA | NA | NA | NA | 14181 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yi | NA | NA | NA | NA | 8781 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yi | NA | NA | NA | NA | 10965 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yin | NA | NA | NA | NA | 12235 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yin | NA | NA | NA | NA | 13483 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yin | NA | NA | NA | NA | 15167 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yuan | NA | NA | NA | NA | 4980 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yuan | NA | NA | NA | NA | 9732 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Yuan | NA | NA | NA | NA | 11287 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zeng | NA | NA | NA | NA | 6620 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zeng | NA | NA | NA | NA | 6845 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zeng | NA | NA | NA | NA | 10889 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zeng | NA | NA | NA | NA | 13427 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhang | NA | NA | NA | NA | 2242 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhang | NA | NA | NA | NA | 9490 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhao | NA | NA | NA | NA | 5365 | NA | Diamond Dusk | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhao | NA | NA | NA | NA | 12957 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zheng | NA | NA | NA | NA | 1316 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zheng | NA | NA | NA | NA | 9998 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zheng | NA | NA | NA | NA | 11374 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhong | NA | NA | NA | NA | 2749 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhong | NA | NA | NA | NA | 6121 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhong | NA | NA | NA | NA | 11783 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhong | NA | NA | NA | NA | 12491 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhong | NA | NA | NA | NA | 15866 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhou | NA | NA | NA | NA | 654 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhou | NA | NA | NA | NA | 3069 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhou | NA | NA | NA | NA | 4255 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhou | NA | NA | NA | NA | 8908 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Guiying Zhou | NA | NA | NA | NA | 15459 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Hanako Yamaguchi | NA | NA | NA | NA | 9842 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Hanako Yamaguchi | NA | NA | NA | NA | 13314 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Honeydew Harmony | NA | NA | NA | NA | 1285 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Honeydew Harmony | NA | NA | NA | NA | 17386 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Indigenous Echo | NA | NA | NA | NA | 1006 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Indigenous Echo | NA | NA | NA | NA | 17381 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | James Jackson | NA | NA | NA | NA | 9370 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | James Jackson | NA | NA | NA | NA | 9989 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | James Taylor | NA | NA | NA | NA | 43 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | James Taylor | NA | NA | NA | NA | 14409 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | James Williams | NA | NA | NA | NA | 2116 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | James Williams | NA | NA | NA | NA | 10231 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jamie Roberts | NA | NA | NA | NA | 12790 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jamie Roberts | NA | NA | NA | NA | 12951 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jason Roberts | NA | NA | NA | NA | 602 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jason Roberts | NA | NA | NA | NA | 11607 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jennifer Diaz | NA | NA | NA | NA | 6613 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jennifer Diaz | NA | NA | NA | NA | 9556 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jennifer Hart | NA | NA | NA | NA | 4159 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jennifer Hart | NA | NA | NA | NA | 7750 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jessica Lewis | NA | NA | NA | NA | 15846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jessica Lewis | NA | NA | NA | NA | 16342 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cai | NA | NA | NA | NA | 714 | NA | Lotus Grey | NA | FALSE | FALSE | FALSE |
| Person | Jie Cai | NA | NA | NA | NA | 1871 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cai | NA | NA | NA | NA | 5925 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cao | NA | NA | NA | NA | 3788 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cao | NA | NA | NA | NA | 5047 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cao | NA | NA | NA | NA | 6649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cao | NA | NA | NA | NA | 9920 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cao | NA | NA | NA | NA | 13617 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cao | NA | NA | NA | NA | 14054 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cheng | NA | NA | NA | NA | 9211 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cheng | NA | NA | NA | NA | 12165 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cheng | NA | NA | NA | NA | 15572 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cui | NA | NA | NA | NA | 863 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cui | NA | NA | NA | NA | 1438 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cui | NA | NA | NA | NA | 8400 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Cui | NA | NA | NA | NA | 9698 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Dai | NA | NA | NA | NA | 2612 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Dai | NA | NA | NA | NA | 14722 | NA | CR¥STAL | NA | FALSE | FALSE | FALSE |
| Person | Jie Deng | NA | NA | NA | NA | 1360 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Deng | NA | NA | NA | NA | 2014 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Deng | NA | NA | NA | NA | 11147 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Ding | NA | NA | NA | NA | 3226 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Ding | NA | NA | NA | NA | 12297 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Ding | NA | NA | NA | NA | 14166 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Dong | NA | NA | NA | NA | 9268 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Dong | NA | NA | NA | NA | 10277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Dong | NA | NA | NA | NA | 11261 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Dong | NA | NA | NA | NA | 16196 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Du | NA | NA | NA | NA | 6900 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Du | NA | NA | NA | NA | 12325 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Du | NA | NA | NA | NA | 14922 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Duan | NA | NA | NA | NA | 13247 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Duan | NA | NA | NA | NA | 13306 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fan | NA | NA | NA | NA | 891 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fan | NA | NA | NA | NA | 5344 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fan | NA | NA | NA | NA | 15090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fang | NA | NA | NA | NA | 3258 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fang | NA | NA | NA | NA | 9447 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fang | NA | NA | NA | NA | 10570 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fang | NA | NA | NA | NA | 11955 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fang | NA | NA | NA | NA | 12542 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Feng | NA | NA | NA | NA | 11045 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Feng | NA | NA | NA | NA | 13917 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Feng | NA | NA | NA | NA | 14540 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Feng | NA | NA | NA | NA | 15663 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fu | NA | NA | NA | NA | 4677 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fu | NA | NA | NA | NA | 6537 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Fu | NA | NA | NA | NA | 13816 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Gu | NA | NA | NA | NA | 647 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Gu | NA | NA | NA | NA | 5446 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Hao | NA | NA | NA | NA | 11710 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Hao | NA | NA | NA | NA | 15011 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Hu | NA | NA | NA | NA | 634 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Hu | NA | NA | NA | NA | 8601 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Hu | NA | NA | NA | NA | 11872 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Huang | NA | NA | NA | NA | 2939 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Huang | NA | NA | NA | NA | 8330 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Huang | NA | NA | NA | NA | 14119 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Jia | NA | NA | NA | NA | 6089 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Jia | NA | NA | NA | NA | 6825 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Jia | NA | NA | NA | NA | 11334 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Jiang | NA | NA | NA | NA | 6939 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Jiang | NA | NA | NA | NA | 7907 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Kang | NA | NA | NA | NA | 2737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Kang | NA | NA | NA | NA | 8324 | NA | The Crystal | NA | FALSE | FALSE | FALSE |
| Person | Jie Kang | NA | NA | NA | NA | 12472 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Lai | NA | NA | NA | NA | 860 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Lai | NA | NA | NA | NA | 1220 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Lai | NA | NA | NA | NA | 7991 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Lai | NA | NA | NA | NA | 9485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Lei | NA | NA | NA | NA | 8252 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Lei | NA | NA | NA | NA | 10191 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Li | NA | NA | NA | NA | 5411 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Li | NA | NA | NA | NA | 6429 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Li | NA | NA | NA | NA | 12525 | NA | Harmonic Paradox | NA | FALSE | FALSE | FALSE |
| Person | Jie Liang | NA | NA | NA | NA | 2583 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Liang | NA | NA | NA | NA | 9128 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Lin | NA | NA | NA | NA | 9670 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Lin | NA | NA | NA | NA | 12766 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Long | NA | NA | NA | NA | 114 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Long | NA | NA | NA | NA | 2845 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Long | NA | NA | NA | NA | 9793 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Long | NA | NA | NA | NA | 16194 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Ma | NA | NA | NA | NA | 2599 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Ma | NA | NA | NA | NA | 8735 | NA | Aurora Vale | NA | FALSE | FALSE | FALSE |
| Person | Jie Ma | NA | NA | NA | NA | 9312 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Mao | NA | NA | NA | NA | 4893 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Mao | NA | NA | NA | NA | 9292 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Mao | NA | NA | NA | NA | 14877 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Meng | NA | NA | NA | NA | 11031 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Meng | NA | NA | NA | NA | 12158 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Qiao | NA | NA | NA | NA | 9760 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Qiao | NA | NA | NA | NA | 15865 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Ren | NA | NA | NA | NA | 6609 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Ren | NA | NA | NA | NA | 12030 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Shao | NA | NA | NA | NA | 862 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Shao | NA | NA | NA | NA | 6907 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Shao | NA | NA | NA | NA | 15941 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Shen | NA | NA | NA | NA | 534 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Shen | NA | NA | NA | NA | 2702 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Shen | NA | NA | NA | NA | 5601 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Song | NA | NA | NA | NA | 2032 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Song | NA | NA | NA | NA | 5852 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Su | NA | NA | NA | NA | 6399 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Su | NA | NA | NA | NA | 7903 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Su | NA | NA | NA | NA | 9595 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Su | NA | NA | NA | NA | 15205 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Su | NA | NA | NA | NA | 15429 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tan | NA | NA | NA | NA | 11437 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tan | NA | NA | NA | NA | 13057 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tan | NA | NA | NA | NA | 16023 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tao | NA | NA | NA | NA | 4259 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tao | NA | NA | NA | NA | 6571 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tao | NA | NA | NA | NA | 8305 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tao | NA | NA | NA | NA | 12552 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tian | NA | NA | NA | NA | 1997 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tian | NA | NA | NA | NA | 6038 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Tian | NA | NA | NA | NA | 15186 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wan | NA | NA | NA | NA | 4471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wan | NA | NA | NA | NA | 8682 | NA | Drew Silver | NA | FALSE | FALSE | FALSE |
| Person | Jie Wan | NA | NA | NA | NA | 9914 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wang | NA | NA | NA | NA | 10225 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wang | NA | NA | NA | NA | 10623 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wang | NA | NA | NA | NA | 11579 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wei | NA | NA | NA | NA | 2916 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wei | NA | NA | NA | NA | 3140 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wei | NA | NA | NA | NA | 3689 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wen | NA | NA | NA | NA | 1160 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wen | NA | NA | NA | NA | 1330 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wen | NA | NA | NA | NA | 5579 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wen | NA | NA | NA | NA | 11822 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wu | NA | NA | NA | NA | 10976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Wu | NA | NA | NA | NA | 11149 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xia | NA | NA | NA | NA | 2262 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xia | NA | NA | NA | NA | 7912 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xie | NA | NA | NA | NA | 2777 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xie | NA | NA | NA | NA | 12484 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xie | NA | NA | NA | NA | 16115 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xu | NA | NA | NA | NA | 6244 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xu | NA | NA | NA | NA | 9321 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xu | NA | NA | NA | NA | 12627 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xu | NA | NA | NA | NA | 14180 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xu | NA | NA | NA | NA | 16281 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Xu | NA | NA | NA | NA | 16536 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yan | NA | NA | NA | NA | 177 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yan | NA | NA | NA | NA | 3290 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yan | NA | NA | NA | NA | 5716 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yan | NA | NA | NA | NA | 8158 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yan | NA | NA | NA | NA | 9610 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yan | NA | NA | NA | NA | 14960 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yao | NA | NA | NA | NA | 537 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yao | NA | NA | NA | NA | 8513 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yao | NA | NA | NA | NA | 12940 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yao | NA | NA | NA | NA | 15667 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yi | NA | NA | NA | NA | 7088 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yi | NA | NA | NA | NA | 8255 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yin | NA | NA | NA | NA | 1592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yin | NA | NA | NA | NA | 6127 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Yin | NA | NA | NA | NA | 9252 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zhang | NA | NA | NA | NA | 2861 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zhang | NA | NA | NA | NA | 6669 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zhang | NA | NA | NA | NA | 7091 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zheng | NA | NA | NA | NA | 573 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zheng | NA | NA | NA | NA | 648 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zheng | NA | NA | NA | NA | 3515 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zheng | NA | NA | NA | NA | 3582 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zheng | NA | NA | NA | NA | 8206 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zhu | NA | NA | NA | NA | 984 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zhu | NA | NA | NA | NA | 6808 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zou | NA | NA | NA | NA | 2416 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zou | NA | NA | NA | NA | 2885 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zou | NA | NA | NA | NA | 2917 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zou | NA | NA | NA | NA | 9415 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jie Zou | NA | NA | NA | NA | 13102 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Cao | NA | NA | NA | NA | 12343 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Cao | NA | NA | NA | NA | 15204 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Chang | NA | NA | NA | NA | 1692 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Chang | NA | NA | NA | NA | 2218 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Chang | NA | NA | NA | NA | 15021 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Cui | NA | NA | NA | NA | 1074 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Cui | NA | NA | NA | NA | 9146 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Cui | NA | NA | NA | NA | 9956 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Cui | NA | NA | NA | NA | 13814 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Dai | NA | NA | NA | NA | 8414 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Dai | NA | NA | NA | NA | 12037 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ding | NA | NA | NA | NA | 1875 | NA | Solara | NA | FALSE | FALSE | FALSE |
| Person | Jing Ding | NA | NA | NA | NA | 10528 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ding | NA | NA | NA | NA | 12280 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Dong | NA | NA | NA | NA | 9477 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Dong | NA | NA | NA | NA | 10987 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Du | NA | NA | NA | NA | 6815 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Du | NA | NA | NA | NA | 14130 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Du | NA | NA | NA | NA | 14649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Duan | NA | NA | NA | NA | 8433 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Duan | NA | NA | NA | NA | 12349 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Duan | NA | NA | NA | NA | 13507 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Duan | NA | NA | NA | NA | 13878 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Fang | NA | NA | NA | NA | 7082 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Fang | NA | NA | NA | NA | 12670 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Feng | NA | NA | NA | NA | 5404 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Feng | NA | NA | NA | NA | 15655 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Gao | NA | NA | NA | NA | 5435 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Gao | NA | NA | NA | NA | 13696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Gao | NA | NA | NA | NA | 16568 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Gong | NA | NA | NA | NA | 8449 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Gong | NA | NA | NA | NA | 10164 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Gong | NA | NA | NA | NA | 13745 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Gu | NA | NA | NA | NA | 5836 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Gu | NA | NA | NA | NA | 12520 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Guo | NA | NA | NA | NA | 7446 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Guo | NA | NA | NA | NA | 7453 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Guo | NA | NA | NA | NA | 8933 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Guo | NA | NA | NA | NA | 11323 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Guo | NA | NA | NA | NA | 14042 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Guo | NA | NA | NA | NA | 16013 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Han | NA | NA | NA | NA | 211 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Han | NA | NA | NA | NA | 2600 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Han | NA | NA | NA | NA | 13406 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing He | NA | NA | NA | NA | 15871 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing He | NA | NA | NA | NA | 16523 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Hou | NA | NA | NA | NA | 1554 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Hou | NA | NA | NA | NA | 7198 | NA | Vortex Cantata | NA | FALSE | FALSE | FALSE |
| Person | Jing Hu | NA | NA | NA | NA | 13815 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Hu | NA | NA | NA | NA | 15264 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Huang | NA | NA | NA | NA | 2270 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Huang | NA | NA | NA | NA | 7079 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Jia | NA | NA | NA | NA | 6863 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Jia | NA | NA | NA | NA | 11118 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Jiang | NA | NA | NA | NA | 14919 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Jiang | NA | NA | NA | NA | 15382 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Jin | NA | NA | NA | NA | 2721 | NA | LIL OMEGA | NA | FALSE | FALSE | FALSE |
| Person | Jing Jin | NA | NA | NA | NA | 3399 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Jin | NA | NA | NA | NA | 9210 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kang | NA | NA | NA | NA | 878 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kang | NA | NA | NA | NA | 1348 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kang | NA | NA | NA | NA | 4327 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kang | NA | NA | NA | NA | 6258 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kang | NA | NA | NA | NA | 13828 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kang | NA | NA | NA | NA | 14650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kong | NA | NA | NA | NA | 9968 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kong | NA | NA | NA | NA | 10298 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Kong | NA | NA | NA | NA | 12580 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lai | NA | NA | NA | NA | 5268 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lai | NA | NA | NA | NA | 8204 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lai | NA | NA | NA | NA | 9333 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lai | NA | NA | NA | NA | 10113 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lai | NA | NA | NA | NA | 14327 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lei | NA | NA | NA | NA | 2275 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lei | NA | NA | NA | NA | 4486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lei | NA | NA | NA | NA | 15563 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Li | NA | NA | NA | NA | 10887 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Li | NA | NA | NA | NA | 14845 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Liao | NA | NA | NA | NA | 7292 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Liao | NA | NA | NA | NA | 7397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Liao | NA | NA | NA | NA | 16168 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lin | NA | NA | NA | NA | 1245 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lin | NA | NA | NA | NA | 2251 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lin | NA | NA | NA | NA | 4487 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lin | NA | NA | NA | NA | 9254 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lin | NA | NA | NA | NA | 11687 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Long | NA | NA | NA | NA | 1967 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Long | NA | NA | NA | NA | 4708 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Long | NA | NA | NA | NA | 7967 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Long | NA | NA | NA | NA | 7984 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Long | NA | NA | NA | NA | 12208 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lu | NA | NA | NA | NA | 8188 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Lu | NA | NA | NA | NA | 11879 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Luo | NA | NA | NA | NA | 9045 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Luo | NA | NA | NA | NA | 15273 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ma | NA | NA | NA | NA | 2977 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ma | NA | NA | NA | NA | 15484 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Mao | NA | NA | NA | NA | 7215 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Mao | NA | NA | NA | NA | 11820 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Mao | NA | NA | NA | NA | 12207 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Meng | NA | NA | NA | NA | 3142 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Meng | NA | NA | NA | NA | 8030 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Meng | NA | NA | NA | NA | 10040 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Pan | NA | NA | NA | NA | 7537 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Pan | NA | NA | NA | NA | 9738 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Pan | NA | NA | NA | NA | 11030 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Pan | NA | NA | NA | NA | 13058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qian | NA | NA | NA | NA | 2162 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qian | NA | NA | NA | NA | 4891 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qian | NA | NA | NA | NA | 7764 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qian | NA | NA | NA | NA | 10026 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qin | NA | NA | NA | NA | 894 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qin | NA | NA | NA | NA | 1222 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qin | NA | NA | NA | NA | 6012 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qiu | NA | NA | NA | NA | 4292 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Qiu | NA | NA | NA | NA | 8329 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ren | NA | NA | NA | NA | 854 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ren | NA | NA | NA | NA | 3655 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ren | NA | NA | NA | NA | 6232 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ren | NA | NA | NA | NA | 6601 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Ren | NA | NA | NA | NA | 10568 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Shen | NA | NA | NA | NA | 10495 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Shen | NA | NA | NA | NA | 11760 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Shen | NA | NA | NA | NA | 14558 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Shi | NA | NA | NA | NA | 4220 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Shi | NA | NA | NA | NA | 9609 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Song | NA | NA | NA | NA | 10012 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Song | NA | NA | NA | NA | 12050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Song | NA | NA | NA | NA | 12717 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Song | NA | NA | NA | NA | 15718 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Su | NA | NA | NA | NA | 13278 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Su | NA | NA | NA | NA | 16417 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Sun | NA | NA | NA | NA | 2396 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Sun | NA | NA | NA | NA | 6567 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tan | NA | NA | NA | NA | 2012 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tan | NA | NA | NA | NA | 10779 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tan | NA | NA | NA | NA | 11430 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tan | NA | NA | NA | NA | 12889 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tan | NA | NA | NA | NA | 15873 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tang | NA | NA | NA | NA | 4238 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tang | NA | NA | NA | NA | 7592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tang | NA | NA | NA | NA | 12713 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tian | NA | NA | NA | NA | 817 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tian | NA | NA | NA | NA | 1831 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tian | NA | NA | NA | NA | 2165 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tian | NA | NA | NA | NA | 5355 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tian | NA | NA | NA | NA | 10364 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tian | NA | NA | NA | NA | 12669 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Tian | NA | NA | NA | NA | 12671 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wang | NA | NA | NA | NA | 3158 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wang | NA | NA | NA | NA | 5031 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wang | NA | NA | NA | NA | 8738 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wang | NA | NA | NA | NA | 10811 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wang | NA | NA | NA | NA | 11455 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wei | NA | NA | NA | NA | 5508 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wei | NA | NA | NA | NA | 8652 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wei | NA | NA | NA | NA | 9796 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wu | NA | NA | NA | NA | 12372 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Wu | NA | NA | NA | NA | 16700 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Xia | NA | NA | NA | NA | 6549 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Xia | NA | NA | NA | NA | 14448 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Xiang | NA | NA | NA | NA | 5358 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Xiang | NA | NA | NA | NA | 5732 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Xiao | NA | NA | NA | NA | 9575 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Xiao | NA | NA | NA | NA | 16060 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Xie | NA | NA | NA | NA | 3446 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Xie | NA | NA | NA | NA | 9238 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yang | NA | NA | NA | NA | 392 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yang | NA | NA | NA | NA | 469 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yang | NA | NA | NA | NA | 11073 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yao | NA | NA | NA | NA | 6841 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yao | NA | NA | NA | NA | 16071 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yi | NA | NA | NA | NA | 2240 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yi | NA | NA | NA | NA | 7620 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yi | NA | NA | NA | NA | 7718 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Yin | NA | NA | NA | NA | 2455 | NA | Venice | NA | FALSE | FALSE | FALSE |
| Person | Jing Yin | NA | NA | NA | NA | 5363 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhang | NA | NA | NA | NA | 3012 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhang | NA | NA | NA | NA | 3807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhang | NA | NA | NA | NA | 12557 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhang | NA | NA | NA | NA | 16503 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhong | NA | NA | NA | NA | 230 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhong | NA | NA | NA | NA | 1683 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhong | NA | NA | NA | NA | 2665 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhong | NA | NA | NA | NA | 5177 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhong | NA | NA | NA | NA | 8462 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhu | NA | NA | NA | NA | 3486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhu | NA | NA | NA | NA | 3916 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zhu | NA | NA | NA | NA | 14123 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zou | NA | NA | NA | NA | 7794 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zou | NA | NA | NA | NA | 9407 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jing Zou | NA | NA | NA | NA | 9476 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | John Rogers | NA | NA | NA | NA | 3499 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | John Rogers | NA | NA | NA | NA | 8466 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jonathan Wade | NA | NA | NA | NA | 1562 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jonathan Wade | NA | NA | NA | NA | 2405 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Bai | NA | NA | NA | NA | 10013 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Bai | NA | NA | NA | NA | 12511 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cai | NA | NA | NA | NA | 242 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cai | NA | NA | NA | NA | 2833 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cai | NA | NA | NA | NA | 6199 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cao | NA | NA | NA | NA | 2844 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cao | NA | NA | NA | NA | 10556 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cao | NA | NA | NA | NA | 10734 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cao | NA | NA | NA | NA | 15413 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cao | NA | NA | NA | NA | 16198 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Chen | NA | NA | NA | NA | 8461 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Chen | NA | NA | NA | NA | 12560 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Chen | NA | NA | NA | NA | 16087 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cheng | NA | NA | NA | NA | 9741 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cheng | NA | NA | NA | NA | 15238 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Cheng | NA | NA | NA | NA | 15695 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Dai | NA | NA | NA | NA | 10827 | NA | Marco Sun | NA | FALSE | FALSE | FALSE |
| Person | Juan Dai | NA | NA | NA | NA | 13506 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Deng | NA | NA | NA | NA | 6123 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Deng | NA | NA | NA | NA | 9573 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ding | NA | NA | NA | NA | 3182 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ding | NA | NA | NA | NA | 4182 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ding | NA | NA | NA | NA | 4317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ding | NA | NA | NA | NA | 5403 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Dong | NA | NA | NA | NA | 8167 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Dong | NA | NA | NA | NA | 10638 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Dong | NA | NA | NA | NA | 13195 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Dong | NA | NA | NA | NA | 14199 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Dong | NA | NA | NA | NA | 15115 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Du | NA | NA | NA | NA | 6636 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Du | NA | NA | NA | NA | 15187 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Du | NA | NA | NA | NA | 15777 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Duan | NA | NA | NA | NA | 3475 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Duan | NA | NA | NA | NA | 7649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Duan | NA | NA | NA | NA | 9099 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Duan | NA | NA | NA | NA | 15701 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fan | NA | NA | NA | NA | 8381 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fan | NA | NA | NA | NA | 8618 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fan | NA | NA | NA | NA | 13731 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fang | NA | NA | NA | NA | 4745 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fang | NA | NA | NA | NA | 16403 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fang | NA | NA | NA | NA | 16599 | NA | Atlas & The Echoes | NA | FALSE | FALSE | FALSE |
| Person | Juan Feng | NA | NA | NA | NA | 75 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Feng | NA | NA | NA | NA | 1518 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Feng | NA | NA | NA | NA | 5367 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fu | NA | NA | NA | NA | 1602 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fu | NA | NA | NA | NA | 3902 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fu | NA | NA | NA | NA | 7401 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Fu | NA | NA | NA | NA | 8129 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Gao | NA | NA | NA | NA | 434 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Gao | NA | NA | NA | NA | 1844 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Gao | NA | NA | NA | NA | 14850 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Gu | NA | NA | NA | NA | 7521 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Gu | NA | NA | NA | NA | 14721 | NA | Sage XII | NA | FALSE | FALSE | FALSE |
| Person | Juan Hao | NA | NA | NA | NA | 13726 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Hao | NA | NA | NA | NA | 14549 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan He | NA | NA | NA | NA | 814 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan He | NA | NA | NA | NA | 12878 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Hou | NA | NA | NA | NA | 9248 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Hou | NA | NA | NA | NA | 16361 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Hu | NA | NA | NA | NA | 426 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Hu | NA | NA | NA | NA | 1082 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Hu | NA | NA | NA | NA | 4307 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Jia | NA | NA | NA | NA | 207 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Jia | NA | NA | NA | NA | 4971 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Jia | NA | NA | NA | NA | 7674 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Jin | NA | NA | NA | NA | 4548 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Jin | NA | NA | NA | NA | 6485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Jin | NA | NA | NA | NA | 13284 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Kang | NA | NA | NA | NA | 908 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Kang | NA | NA | NA | NA | 10724 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Kang | NA | NA | NA | NA | 11475 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Kang | NA | NA | NA | NA | 15573 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Kang | NA | NA | NA | NA | 16220 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lai | NA | NA | NA | NA | 2016 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lai | NA | NA | NA | NA | 5377 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lai | NA | NA | NA | NA | 9136 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lai | NA | NA | NA | NA | 15665 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lei | NA | NA | NA | NA | 2637 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lei | NA | NA | NA | NA | 6311 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lei | NA | NA | NA | NA | 16684 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Li | NA | NA | NA | NA | 2447 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Li | NA | NA | NA | NA | 3448 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Li | NA | NA | NA | NA | 3575 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Li | NA | NA | NA | NA | 7342 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Li | NA | NA | NA | NA | 10418 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Li | NA | NA | NA | NA | 14208 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Li | NA | NA | NA | NA | 14870 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Liu | NA | NA | NA | NA | 5902 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Liu | NA | NA | NA | NA | 9970 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Liu | NA | NA | NA | NA | 13951 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Liu | NA | NA | NA | NA | 16091 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Long | NA | NA | NA | NA | 296 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Long | NA | NA | NA | NA | 9847 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lu | NA | NA | NA | NA | 11253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Lu | NA | NA | NA | NA | 12745 | NA | DA STORM | NA | FALSE | FALSE | FALSE |
| Person | Juan Luo | NA | NA | NA | NA | 133 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Luo | NA | NA | NA | NA | 452 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ma | NA | NA | NA | NA | 2091 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ma | NA | NA | NA | NA | 7093 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Mao | NA | NA | NA | NA | 10581 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Mao | NA | NA | NA | NA | 14718 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Mao | NA | NA | NA | NA | 14844 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Meng | NA | NA | NA | NA | 366 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Meng | NA | NA | NA | NA | 1289 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Meng | NA | NA | NA | NA | 1555 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Meng | NA | NA | NA | NA | 2834 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Mo | NA | NA | NA | NA | 2569 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Mo | NA | NA | NA | NA | 3010 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Mo | NA | NA | NA | NA | 4246 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Pan | NA | NA | NA | NA | 2441 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Pan | NA | NA | NA | NA | 2693 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Pan | NA | NA | NA | NA | 4463 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Pan | NA | NA | NA | NA | 8829 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Pan | NA | NA | NA | NA | 10501 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Peng | NA | NA | NA | NA | 1000 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Peng | NA | NA | NA | NA | 4037 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Qian | NA | NA | NA | NA | 1516 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Qian | NA | NA | NA | NA | 5894 | NA | Halcyon | NA | FALSE | FALSE | FALSE |
| Person | Juan Qiao | NA | NA | NA | NA | 3957 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Qiao | NA | NA | NA | NA | 5612 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Qiu | NA | NA | NA | NA | 857 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Qiu | NA | NA | NA | NA | 3469 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Qiu | NA | NA | NA | NA | 5346 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Qiu | NA | NA | NA | NA | 9965 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ren | NA | NA | NA | NA | 10778 | NA | Nate Bishop | NA | FALSE | FALSE | FALSE |
| Person | Juan Ren | NA | NA | NA | NA | 15862 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shao | NA | NA | NA | NA | 3058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shao | NA | NA | NA | NA | 7692 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shao | NA | NA | NA | NA | 8737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shen | NA | NA | NA | NA | 7436 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shen | NA | NA | NA | NA | 9409 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shi | NA | NA | NA | NA | 505 | NA | Storm | NA | FALSE | FALSE | FALSE |
| Person | Juan Shi | NA | NA | NA | NA | 1947 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shi | NA | NA | NA | NA | 3321 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shi | NA | NA | NA | NA | 15224 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shi | NA | NA | NA | NA | 15619 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Shi | NA | NA | NA | NA | 16611 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Song | NA | NA | NA | NA | 9394 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Song | NA | NA | NA | NA | 9994 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Song | NA | NA | NA | NA | 11461 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Song | NA | NA | NA | NA | 12252 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Su | NA | NA | NA | NA | 8166 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Su | NA | NA | NA | NA | 11462 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Su | NA | NA | NA | NA | 12734 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Sun | NA | NA | NA | NA | 204 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Sun | NA | NA | NA | NA | 7071 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Sun | NA | NA | NA | NA | 14971 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Sun | NA | NA | NA | NA | 15801 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Tan | NA | NA | NA | NA | 3298 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Tan | NA | NA | NA | NA | 6539 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Tan | NA | NA | NA | NA | 8926 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Tan | NA | NA | NA | NA | 14168 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Tao | NA | NA | NA | NA | 3312 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Tao | NA | NA | NA | NA | 4974 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Tao | NA | NA | NA | NA | 8165 | NA | Mikey James | NA | FALSE | FALSE | FALSE |
| Person | Juan Wan | NA | NA | NA | NA | 8325 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wan | NA | NA | NA | NA | 16062 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wang | NA | NA | NA | NA | 1400 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wang | NA | NA | NA | NA | 8459 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wei | NA | NA | NA | NA | 771 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wei | NA | NA | NA | NA | 2253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wei | NA | NA | NA | NA | 8719 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wei | NA | NA | NA | NA | 13109 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wen | NA | NA | NA | NA | 2154 | NA | Shadow Fox | NA | FALSE | FALSE | FALSE |
| Person | Juan Wen | NA | NA | NA | NA | 8665 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wen | NA | NA | NA | NA | 9941 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wen | NA | NA | NA | NA | 16250 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wu | NA | NA | NA | NA | 3230 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wu | NA | NA | NA | NA | 4820 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wu | NA | NA | NA | NA | 6880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wu | NA | NA | NA | NA | 8463 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Wu | NA | NA | NA | NA | 14776 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xia | NA | NA | NA | NA | 4114 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xia | NA | NA | NA | NA | 4254 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xia | NA | NA | NA | NA | 6607 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiang | NA | NA | NA | NA | 7440 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiang | NA | NA | NA | NA | 13059 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiang | NA | NA | NA | NA | 15122 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiang | NA | NA | NA | NA | 16197 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiao | NA | NA | NA | NA | 819 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiao | NA | NA | NA | NA | 4305 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiao | NA | NA | NA | NA | 5510 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiao | NA | NA | NA | NA | 14214 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiao | NA | NA | NA | NA | 16065 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiong | NA | NA | NA | NA | 471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiong | NA | NA | NA | NA | 8297 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xiong | NA | NA | NA | NA | 9764 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xu | NA | NA | NA | NA | 435 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xu | NA | NA | NA | NA | 881 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xu | NA | NA | NA | NA | 15110 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xue | NA | NA | NA | NA | 1899 | NA | Velvet Alibi | NA | FALSE | FALSE | FALSE |
| Person | Juan Xue | NA | NA | NA | NA | 4072 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xue | NA | NA | NA | NA | 10025 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Xue | NA | NA | NA | NA | 14433 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yan | NA | NA | NA | NA | 567 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yan | NA | NA | NA | NA | 3463 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yang | NA | NA | NA | NA | 12246 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yang | NA | NA | NA | NA | 14093 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yao | NA | NA | NA | NA | 1589 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yao | NA | NA | NA | NA | 2138 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yao | NA | NA | NA | NA | 4597 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yao | NA | NA | NA | NA | 6101 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yao | NA | NA | NA | NA | 8745 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yao | NA | NA | NA | NA | 12103 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ye | NA | NA | NA | NA | 7353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ye | NA | NA | NA | NA | 9838 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Ye | NA | NA | NA | NA | 12984 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yin | NA | NA | NA | NA | 355 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yin | NA | NA | NA | NA | 2399 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yin | NA | NA | NA | NA | 10292 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yin | NA | NA | NA | NA | 10967 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yin | NA | NA | NA | NA | 12339 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yu | NA | NA | NA | NA | 1492 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yu | NA | NA | NA | NA | 8743 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yu | NA | NA | NA | NA | 9425 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yuan | NA | NA | NA | NA | 2304 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yuan | NA | NA | NA | NA | 10735 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Yuan | NA | NA | NA | NA | 16293 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zeng | NA | NA | NA | NA | 536 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zeng | NA | NA | NA | NA | 2692 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhang | NA | NA | NA | NA | 1311 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhang | NA | NA | NA | NA | 13294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhang | NA | NA | NA | NA | 15750 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zheng | NA | NA | NA | NA | 1158 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zheng | NA | NA | NA | NA | 6237 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhong | NA | NA | NA | NA | 2877 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhong | NA | NA | NA | NA | 3129 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhong | NA | NA | NA | NA | 10546 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhong | NA | NA | NA | NA | 12431 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhong | NA | NA | NA | NA | 15692 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhou | NA | NA | NA | NA | 3882 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhou | NA | NA | NA | NA | 5578 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhou | NA | NA | NA | NA | 15668 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhu | NA | NA | NA | NA | 368 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhu | NA | NA | NA | NA | 3901 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zhu | NA | NA | NA | NA | 8932 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zou | NA | NA | NA | NA | 2024 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Juan Zou | NA | NA | NA | NA | 13937 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Bai | NA | NA | NA | NA | 14950 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Bai | NA | NA | NA | NA | 16735 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cai | NA | NA | NA | NA | 6608 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cai | NA | NA | NA | NA | 14949 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cao | NA | NA | NA | NA | 450 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cao | NA | NA | NA | NA | 12607 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cao | NA | NA | NA | NA | 14486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Chang | NA | NA | NA | NA | 3157 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Chang | NA | NA | NA | NA | 14926 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Chen | NA | NA | NA | NA | 7485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Chen | NA | NA | NA | NA | 8091 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Chen | NA | NA | NA | NA | 13935 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cui | NA | NA | NA | NA | 591 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cui | NA | NA | NA | NA | 1976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cui | NA | NA | NA | NA | 2715 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Cui | NA | NA | NA | NA | 6378 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Dai | NA | NA | NA | NA | 5831 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Dai | NA | NA | NA | NA | 9137 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Dai | NA | NA | NA | NA | 9380 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Dai | NA | NA | NA | NA | 11596 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Deng | NA | NA | NA | NA | 3615 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Deng | NA | NA | NA | NA | 12672 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Deng | NA | NA | NA | NA | 14848 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Ding | NA | NA | NA | NA | 7536 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Ding | NA | NA | NA | NA | 8873 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Ding | NA | NA | NA | NA | 10738 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Du | NA | NA | NA | NA | 741 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Du | NA | NA | NA | NA | 6599 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Du | NA | NA | NA | NA | 16362 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Duan | NA | NA | NA | NA | 6015 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Duan | NA | NA | NA | NA | 9291 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Duan | NA | NA | NA | NA | 10049 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Duan | NA | NA | NA | NA | 15256 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Duan | NA | NA | NA | NA | 15330 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Fang | NA | NA | NA | NA | 4418 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Fang | NA | NA | NA | NA | 6225 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Fang | NA | NA | NA | NA | 12970 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Feng | NA | NA | NA | NA | 6710 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Feng | NA | NA | NA | NA | 8702 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Feng | NA | NA | NA | NA | 9950 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Fu | NA | NA | NA | NA | 6452 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Fu | NA | NA | NA | NA | 10039 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Fu | NA | NA | NA | NA | 10890 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Fu | NA | NA | NA | NA | 13187 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gao | NA | NA | NA | NA | 2338 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gao | NA | NA | NA | NA | 7523 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gao | NA | NA | NA | NA | 13474 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gong | NA | NA | NA | NA | 4765 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gong | NA | NA | NA | NA | 5528 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gong | NA | NA | NA | NA | 13572 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gong | NA | NA | NA | NA | 14318 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gong | NA | NA | NA | NA | 15268 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gu | NA | NA | NA | NA | 87 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Gu | NA | NA | NA | NA | 3581 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Guo | NA | NA | NA | NA | 1900 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Guo | NA | NA | NA | NA | 3033 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Guo | NA | NA | NA | NA | 5864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Guo | NA | NA | NA | NA | 11326 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Han | NA | NA | NA | NA | 4678 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Han | NA | NA | NA | NA | 8623 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Han | NA | NA | NA | NA | 9101 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Han | NA | NA | NA | NA | 14133 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Han | NA | NA | NA | NA | 16526 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Hao | NA | NA | NA | NA | 4975 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Hao | NA | NA | NA | NA | 6371 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Hao | NA | NA | NA | NA | 8503 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Hao | NA | NA | NA | NA | 10591 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun He | NA | NA | NA | NA | 2085 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun He | NA | NA | NA | NA | 9921 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Hu | NA | NA | NA | NA | 4036 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Hu | NA | NA | NA | NA | 8810 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Hu | NA | NA | NA | NA | 13514 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Huang | NA | NA | NA | NA | 4705 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Huang | NA | NA | NA | NA | 9026 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Huang | NA | NA | NA | NA | 11790 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Huang | NA | NA | NA | NA | 15195 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jia | NA | NA | NA | NA | 4732 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jia | NA | NA | NA | NA | 9969 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jia | NA | NA | NA | NA | 13847 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jiang | NA | NA | NA | NA | 811 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jiang | NA | NA | NA | NA | 907 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jiang | NA | NA | NA | NA | 6647 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jiang | NA | NA | NA | NA | 10526 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jiang | NA | NA | NA | NA | 11650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jiang | NA | NA | NA | NA | 16106 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jin | NA | NA | NA | NA | 3959 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jin | NA | NA | NA | NA | 11120 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jin | NA | NA | NA | NA | 12575 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Jin | NA | NA | NA | NA | 12913 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Kong | NA | NA | NA | NA | 8032 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Kong | NA | NA | NA | NA | 10293 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Lai | NA | NA | NA | NA | 8617 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Lai | NA | NA | NA | NA | 15020 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Liang | NA | NA | NA | NA | 4543 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Liang | NA | NA | NA | NA | 7843 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Liang | NA | NA | NA | NA | 8784 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Lin | NA | NA | NA | NA | 2083 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Lin | NA | NA | NA | NA | 3364 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Lin | NA | NA | NA | NA | 14467 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Lin | NA | NA | NA | NA | 15006 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Liu | NA | NA | NA | NA | 4304 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Liu | NA | NA | NA | NA | 12614 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Long | NA | NA | NA | NA | 12523 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Long | NA | NA | NA | NA | 13598 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Luo | NA | NA | NA | NA | 4119 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Luo | NA | NA | NA | NA | 5572 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Luo | NA | NA | NA | NA | 6961 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Luo | NA | NA | NA | NA | 13894 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Mao | NA | NA | NA | NA | 2563 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Mao | NA | NA | NA | NA | 2588 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Mao | NA | NA | NA | NA | 4344 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Mao | NA | NA | NA | NA | 10922 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Mao | NA | NA | NA | NA | 12853 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Mao | NA | NA | NA | NA | 13684 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Meng | NA | NA | NA | NA | 3156 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Meng | NA | NA | NA | NA | 6918 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Meng | NA | NA | NA | NA | 9016 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Meng | NA | NA | NA | NA | 9142 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Meng | NA | NA | NA | NA | 11434 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Meng | NA | NA | NA | NA | 13410 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Meng | NA | NA | NA | NA | 13752 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Mo | NA | NA | NA | NA | 3928 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Mo | NA | NA | NA | NA | 9331 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Pan | NA | NA | NA | NA | 4416 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Pan | NA | NA | NA | NA | 5451 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Pan | NA | NA | NA | NA | 13442 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Peng | NA | NA | NA | NA | 7003 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Peng | NA | NA | NA | NA | 15880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Peng | NA | NA | NA | NA | 16438 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Qiao | NA | NA | NA | NA | 2830 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Qiao | NA | NA | NA | NA | 3989 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Qiao | NA | NA | NA | NA | 6066 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Qin | NA | NA | NA | NA | 8556 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Qin | NA | NA | NA | NA | 11965 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Qin | NA | NA | NA | NA | 12433 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Qiu | NA | NA | NA | NA | 470 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Qiu | NA | NA | NA | NA | 11915 | NA | BLAKK RAYN | NA | FALSE | FALSE | FALSE |
| Person | Jun Shao | NA | NA | NA | NA | 3678 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Shao | NA | NA | NA | NA | 4199 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Shao | NA | NA | NA | NA | 6370 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Shao | NA | NA | NA | NA | 10672 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Shao | NA | NA | NA | NA | 16306 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Shen | NA | NA | NA | NA | 4312 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Shen | NA | NA | NA | NA | 10462 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Shen | NA | NA | NA | NA | 16350 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Shi | NA | NA | NA | NA | 13547 | NA | Mars | NA | FALSE | FALSE | FALSE |
| Person | Jun Shi | NA | NA | NA | NA | 15545 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Song | NA | NA | NA | NA | 388 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Song | NA | NA | NA | NA | 6259 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Song | NA | NA | NA | NA | 6438 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Su | NA | NA | NA | NA | 6580 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Su | NA | NA | NA | NA | 8673 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Su | NA | NA | NA | NA | 11336 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Su | NA | NA | NA | NA | 16025 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Tan | NA | NA | NA | NA | 768 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Tan | NA | NA | NA | NA | 16415 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Tian | NA | NA | NA | NA | 6236 | NA | DR3∆M | NA | FALSE | FALSE | FALSE |
| Person | Jun Tian | NA | NA | NA | NA | 8736 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Tian | NA | NA | NA | NA | 10291 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Tian | NA | NA | NA | NA | 13508 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wan | NA | NA | NA | NA | 480 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wan | NA | NA | NA | NA | 1344 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wan | NA | NA | NA | NA | 2317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wan | NA | NA | NA | NA | 13877 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wan | NA | NA | NA | NA | 15058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wang | NA | NA | NA | NA | 1070 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wang | NA | NA | NA | NA | 8982 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wang | NA | NA | NA | NA | 11466 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wang | NA | NA | NA | NA | 12576 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wei | NA | NA | NA | NA | 205 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wei | NA | NA | NA | NA | 7941 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wei | NA | NA | NA | NA | 8730 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wei | NA | NA | NA | NA | 12787 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wen | NA | NA | NA | NA | 1436 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wen | NA | NA | NA | NA | 11761 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Wen | NA | NA | NA | NA | 15863 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xia | NA | NA | NA | NA | 1227 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xia | NA | NA | NA | NA | 1353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xia | NA | NA | NA | NA | 6261 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xiang | NA | NA | NA | NA | 2367 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xiang | NA | NA | NA | NA | 6670 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xiang | NA | NA | NA | NA | 8851 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xie | NA | NA | NA | NA | 6605 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xie | NA | NA | NA | NA | 8896 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xie | NA | NA | NA | NA | 11974 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xie | NA | NA | NA | NA | 13544 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xiong | NA | NA | NA | NA | 2562 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xiong | NA | NA | NA | NA | 5223 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xiong | NA | NA | NA | NA | 6063 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xu | NA | NA | NA | NA | 8883 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Xu | NA | NA | NA | NA | 11098 | NA | Cassie Day | NA | FALSE | FALSE | FALSE |
| Person | Jun Yan | NA | NA | NA | NA | 6354 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yan | NA | NA | NA | NA | 8866 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yan | NA | NA | NA | NA | 14758 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yang | NA | NA | NA | NA | 4236 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yang | NA | NA | NA | NA | 9217 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yao | NA | NA | NA | NA | 212 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yao | NA | NA | NA | NA | 6069 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Ye | NA | NA | NA | NA | 309 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Ye | NA | NA | NA | NA | 3379 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Ye | NA | NA | NA | NA | 7337 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Ye | NA | NA | NA | NA | 9574 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yi | NA | NA | NA | NA | 12271 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yi | NA | NA | NA | NA | 12712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yi | NA | NA | NA | NA | 12814 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yin | NA | NA | NA | NA | 1832 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yin | NA | NA | NA | NA | 3774 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yin | NA | NA | NA | NA | 4558 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yin | NA | NA | NA | NA | 5402 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yin | NA | NA | NA | NA | 10847 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yin | NA | NA | NA | NA | 15086 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yin | NA | NA | NA | NA | 16515 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yu | NA | NA | NA | NA | 1651 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yu | NA | NA | NA | NA | 5388 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yu | NA | NA | NA | NA | 6781 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yu | NA | NA | NA | NA | 8641 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yu | NA | NA | NA | NA | 8817 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yu | NA | NA | NA | NA | 9911 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yu | NA | NA | NA | NA | 10341 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yu | NA | NA | NA | NA | 13137 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yuan | NA | NA | NA | NA | 7236 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yuan | NA | NA | NA | NA | 11657 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Yuan | NA | NA | NA | NA | 16164 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zeng | NA | NA | NA | NA | 942 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zeng | NA | NA | NA | NA | 16201 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zhang | NA | NA | NA | NA | 1199 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zhang | NA | NA | NA | NA | 2766 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zhang | NA | NA | NA | NA | 2973 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zheng | NA | NA | NA | NA | 1606 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zheng | NA | NA | NA | NA | 3057 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zhou | NA | NA | NA | NA | 934 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zhou | NA | NA | NA | NA | 9522 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zhou | NA | NA | NA | NA | 15232 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zhu | NA | NA | NA | NA | 3702 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zhu | NA | NA | NA | NA | 4636 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zou | NA | NA | NA | NA | 2536 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zou | NA | NA | NA | NA | 8180 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Jun Zou | NA | NA | NA | NA | 9740 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Justin Williams | NA | NA | NA | NA | 3338 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Justin Williams | NA | NA | NA | NA | 7356 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Karen Williams | NA | NA | NA | NA | 5164 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Karen Williams | NA | NA | NA | NA | 12639 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Katelyn Johnson | NA | NA | NA | NA | 11516 | NA | Eon | NA | FALSE | FALSE | FALSE |
| Person | Katelyn Johnson | NA | NA | NA | NA | 13355 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kelly Johnson | NA | NA | NA | NA | 8340 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kelly Johnson | NA | NA | NA | NA | 9314 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kenneth Jones | NA | NA | NA | NA | 3207 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kenneth Jones | NA | NA | NA | NA | 13339 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kevin Baker | NA | NA | NA | NA | 5117 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kevin Baker | NA | NA | NA | NA | 8424 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kimberly Brown | NA | NA | NA | NA | 8195 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kimberly Brown | NA | NA | NA | NA | 13454 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kimberly Moore | NA | NA | NA | NA | 9065 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kimberly Moore | NA | NA | NA | NA | 12267 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kimberly Smith | NA | NA | NA | NA | 5160 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Kimberly Smith | NA | NA | NA | NA | 15319 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Laura Brown | NA | NA | NA | NA | 5434 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Laura Brown | NA | NA | NA | NA | 8479 | NA | Hunter Miles | NA | FALSE | FALSE | FALSE |
| Person | Laura Clark | NA | NA | NA | NA | 4683 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Laura Clark | NA | NA | NA | NA | 13479 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lauren Schmitt | NA | NA | NA | NA | 7696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lauren Schmitt | NA | NA | NA | NA | 7924 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Bai | NA | NA | NA | NA | 3155 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Bai | NA | NA | NA | NA | 4244 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Bai | NA | NA | NA | NA | 6992 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Bai | NA | NA | NA | NA | 7426 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Bai | NA | NA | NA | NA | 12485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cai | NA | NA | NA | NA | 11599 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cai | NA | NA | NA | NA | 11694 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cai | NA | NA | NA | NA | 13746 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cao | NA | NA | NA | NA | 3605 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cao | NA | NA | NA | NA | 4422 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cao | NA | NA | NA | NA | 8555 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cao | NA | NA | NA | NA | 13393 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cao | NA | NA | NA | NA | 13738 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cheng | NA | NA | NA | NA | 4983 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cheng | NA | NA | NA | NA | 10112 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cui | NA | NA | NA | NA | 7645 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cui | NA | NA | NA | NA | 8387 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Cui | NA | NA | NA | NA | 15141 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Dai | NA | NA | NA | NA | 3472 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Dai | NA | NA | NA | NA | 4786 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Dai | NA | NA | NA | NA | 10983 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Deng | NA | NA | NA | NA | 6241 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Deng | NA | NA | NA | NA | 7083 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Du | NA | NA | NA | NA | 4323 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Du | NA | NA | NA | NA | 6442 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Duan | NA | NA | NA | NA | 1465 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Duan | NA | NA | NA | NA | 3699 | NA | Static Hymn | NA | FALSE | FALSE | FALSE |
| Person | Lei Duan | NA | NA | NA | NA | 7055 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Duan | NA | NA | NA | NA | 9207 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fan | NA | NA | NA | NA | 655 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fan | NA | NA | NA | NA | 4219 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fan | NA | NA | NA | NA | 11591 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fang | NA | NA | NA | NA | 4455 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fang | NA | NA | NA | NA | 6010 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fang | NA | NA | NA | NA | 7578 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Feng | NA | NA | NA | NA | 1157 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Feng | NA | NA | NA | NA | 6638 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fu | NA | NA | NA | NA | 579 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fu | NA | NA | NA | NA | 818 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fu | NA | NA | NA | NA | 4258 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fu | NA | NA | NA | NA | 6713 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Fu | NA | NA | NA | NA | 12238 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Gao | NA | NA | NA | NA | 8064 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Gao | NA | NA | NA | NA | 11193 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Gong | NA | NA | NA | NA | 2055 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Gong | NA | NA | NA | NA | 9344 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Gong | NA | NA | NA | NA | 11041 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Gong | NA | NA | NA | NA | 15541 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Gong | NA | NA | NA | NA | 15553 | NA | Cameron Fox | NA | FALSE | FALSE | FALSE |
| Person | Lei Gu | NA | NA | NA | NA | 718 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Gu | NA | NA | NA | NA | 1607 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Guo | NA | NA | NA | NA | 3523 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Guo | NA | NA | NA | NA | 10650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei He | NA | NA | NA | NA | 1649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei He | NA | NA | NA | NA | 4637 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei He | NA | NA | NA | NA | 6491 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Hu | NA | NA | NA | NA | 6958 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Hu | NA | NA | NA | NA | 9255 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Hu | NA | NA | NA | NA | 11689 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Huang | NA | NA | NA | NA | 2052 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Huang | NA | NA | NA | NA | 7593 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Huang | NA | NA | NA | NA | 11345 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jia | NA | NA | NA | NA | 8397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jia | NA | NA | NA | NA | 13083 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jia | NA | NA | NA | NA | 15516 | NA | DVRK | NA | FALSE | FALSE | FALSE |
| Person | Lei Jiang | NA | NA | NA | NA | 5149 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jiang | NA | NA | NA | NA | 7783 | NA | BLVE | NA | FALSE | FALSE | FALSE |
| Person | Lei Jiang | NA | NA | NA | NA | 10154 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jiang | NA | NA | NA | NA | 15564 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jin | NA | NA | NA | NA | 1493 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jin | NA | NA | NA | NA | 5520 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jin | NA | NA | NA | NA | 11921 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Jin | NA | NA | NA | NA | 12241 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Kong | NA | NA | NA | NA | 1760 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Kong | NA | NA | NA | NA | 1901 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Kong | NA | NA | NA | NA | 5094 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Kong | NA | NA | NA | NA | 5413 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Lai | NA | NA | NA | NA | 3952 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Lai | NA | NA | NA | NA | 5371 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Lai | NA | NA | NA | NA | 12556 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Li | NA | NA | NA | NA | 4803 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Li | NA | NA | NA | NA | 12653 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Liao | NA | NA | NA | NA | 172 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Liao | NA | NA | NA | NA | 11203 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Liao | NA | NA | NA | NA | 12493 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Liao | NA | NA | NA | NA | 13034 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Lin | NA | NA | NA | NA | 11561 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Lin | NA | NA | NA | NA | 13263 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Lin | NA | NA | NA | NA | 16692 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Liu | NA | NA | NA | NA | 12065 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Liu | NA | NA | NA | NA | 14084 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Long | NA | NA | NA | NA | 3435 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Long | NA | NA | NA | NA | 8603 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Long | NA | NA | NA | NA | 9727 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Long | NA | NA | NA | NA | 10011 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Lu | NA | NA | NA | NA | 10223 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Lu | NA | NA | NA | NA | 16696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Luo | NA | NA | NA | NA | 2483 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Luo | NA | NA | NA | NA | 6135 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Luo | NA | NA | NA | NA | 6519 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Luo | NA | NA | NA | NA | 9519 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Ma | NA | NA | NA | NA | 570 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Ma | NA | NA | NA | NA | 2370 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Ma | NA | NA | NA | NA | 7130 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Ma | NA | NA | NA | NA | 11707 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Ma | NA | NA | NA | NA | 14179 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Pan | NA | NA | NA | NA | 2443 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Pan | NA | NA | NA | NA | 4056 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Peng | NA | NA | NA | NA | 1825 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Peng | NA | NA | NA | NA | 9638 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Peng | NA | NA | NA | NA | 15618 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qian | NA | NA | NA | NA | 6579 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qian | NA | NA | NA | NA | 15146 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qiao | NA | NA | NA | NA | 739 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qiao | NA | NA | NA | NA | 12331 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qiao | NA | NA | NA | NA | 14608 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qin | NA | NA | NA | NA | 2993 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qin | NA | NA | NA | NA | 6081 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qin | NA | NA | NA | NA | 16475 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qiu | NA | NA | NA | NA | 7110 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qiu | NA | NA | NA | NA | 7216 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qiu | NA | NA | NA | NA | 11658 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Qiu | NA | NA | NA | NA | 12258 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Shao | NA | NA | NA | NA | 6916 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Shao | NA | NA | NA | NA | 10583 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Shao | NA | NA | NA | NA | 12277 | NA | Beck | NA | FALSE | FALSE | FALSE |
| Person | Lei Shen | NA | NA | NA | NA | 1940 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Shen | NA | NA | NA | NA | 2970 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Shen | NA | NA | NA | NA | 4397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Shi | NA | NA | NA | NA | 4987 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Shi | NA | NA | NA | NA | 7444 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Shi | NA | NA | NA | NA | 10907 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Su | NA | NA | NA | NA | 11799 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Su | NA | NA | NA | NA | 12551 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Sun | NA | NA | NA | NA | 3696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Sun | NA | NA | NA | NA | 6573 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Sun | NA | NA | NA | NA | 14932 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tan | NA | NA | NA | NA | 6173 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tan | NA | NA | NA | NA | 6280 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tan | NA | NA | NA | NA | 6566 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tan | NA | NA | NA | NA | 6995 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tang | NA | NA | NA | NA | 2210 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tang | NA | NA | NA | NA | 3976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tang | NA | NA | NA | NA | 6829 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tang | NA | NA | NA | NA | 10551 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tang | NA | NA | NA | NA | 14811 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tao | NA | NA | NA | NA | 1868 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tao | NA | NA | NA | NA | 6802 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tao | NA | NA | NA | NA | 13227 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Tao | NA | NA | NA | NA | 15251 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Wan | NA | NA | NA | NA | 7931 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Wan | NA | NA | NA | NA | 14805 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Wan | NA | NA | NA | NA | 16525 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Wang | NA | NA | NA | NA | 5112 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Wang | NA | NA | NA | NA | 6625 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Wei | NA | NA | NA | NA | 1013 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Wei | NA | NA | NA | NA | 16277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xiao | NA | NA | NA | NA | 3434 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xiao | NA | NA | NA | NA | 3653 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xiao | NA | NA | NA | NA | 7499 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xie | NA | NA | NA | NA | 213 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xie | NA | NA | NA | NA | 5369 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xiong | NA | NA | NA | NA | 2375 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xiong | NA | NA | NA | NA | 5071 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xiong | NA | NA | NA | NA | 6618 | NA | A.D. Knight | NA | FALSE | FALSE | FALSE |
| Person | Lei Xue | NA | NA | NA | NA | 185 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xue | NA | NA | NA | NA | 316 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xue | NA | NA | NA | NA | 6325 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xue | NA | NA | NA | NA | 7121 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xue | NA | NA | NA | NA | 10428 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xue | NA | NA | NA | NA | 11747 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Xue | NA | NA | NA | NA | 15427 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yan | NA | NA | NA | NA | 753 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yan | NA | NA | NA | NA | 10472 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yang | NA | NA | NA | NA | 3313 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yang | NA | NA | NA | NA | 4697 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yao | NA | NA | NA | NA | 10401 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yao | NA | NA | NA | NA | 13110 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yao | NA | NA | NA | NA | 16698 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yi | NA | NA | NA | NA | 645 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yi | NA | NA | NA | NA | 1745 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yi | NA | NA | NA | NA | 4810 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yi | NA | NA | NA | NA | 5827 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yi | NA | NA | NA | NA | 5851 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yi | NA | NA | NA | NA | 7772 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yi | NA | NA | NA | NA | 8450 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yi | NA | NA | NA | NA | 13771 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yu | NA | NA | NA | NA | 6666 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yu | NA | NA | NA | NA | 7628 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yuan | NA | NA | NA | NA | 2589 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Yuan | NA | NA | NA | NA | 7633 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zeng | NA | NA | NA | NA | 3195 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zeng | NA | NA | NA | NA | 13281 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhang | NA | NA | NA | NA | 7327 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhang | NA | NA | NA | NA | 12715 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhao | NA | NA | NA | NA | 983 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhao | NA | NA | NA | NA | 11553 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhao | NA | NA | NA | NA | 12658 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhao | NA | NA | NA | NA | 13145 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhao | NA | NA | NA | NA | 13425 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhao | NA | NA | NA | NA | 14998 | NA | Elysian | NA | FALSE | FALSE | FALSE |
| Person | Lei Zheng | NA | NA | NA | NA | 3937 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zheng | NA | NA | NA | NA | 5823 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zheng | NA | NA | NA | NA | 12996 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zheng | NA | NA | NA | NA | 13434 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhong | NA | NA | NA | NA | 4746 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhong | NA | NA | NA | NA | 10781 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhou | NA | NA | NA | NA | 97 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhou | NA | NA | NA | NA | 432 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhou | NA | NA | NA | NA | 2434 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhou | NA | NA | NA | NA | 5175 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhu | NA | NA | NA | NA | 4175 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhu | NA | NA | NA | NA | 8995 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zhu | NA | NA | NA | NA | 16689 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zou | NA | NA | NA | NA | 7162 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lei Zou | NA | NA | NA | NA | 16630 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Bai | NA | NA | NA | NA | 1824 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Bai | NA | NA | NA | NA | 3203 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Bai | NA | NA | NA | NA | 5830 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Bai | NA | NA | NA | NA | 6058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Bai | NA | NA | NA | NA | 14874 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Bai | NA | NA | NA | NA | 16357 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Chang | NA | NA | NA | NA | 1514 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Chang | NA | NA | NA | NA | 7896 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Chang | NA | NA | NA | NA | 15012 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Cheng | NA | NA | NA | NA | 2351 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Cheng | NA | NA | NA | NA | 3441 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Cheng | NA | NA | NA | NA | 11585 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Cheng | NA | NA | NA | NA | 14276 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Cui | NA | NA | NA | NA | 1239 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Cui | NA | NA | NA | NA | 9960 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Cui | NA | NA | NA | NA | 14422 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Deng | NA | NA | NA | NA | 1828 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Deng | NA | NA | NA | NA | 9212 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Deng | NA | NA | NA | NA | 9971 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Deng | NA | NA | NA | NA | 13608 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Deng | NA | NA | NA | NA | 14779 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Deng | NA | NA | NA | NA | 15513 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ding | NA | NA | NA | NA | 7237 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ding | NA | NA | NA | NA | 7625 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Dong | NA | NA | NA | NA | 2532 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Dong | NA | NA | NA | NA | 5812 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Dong | NA | NA | NA | NA | 15022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Dong | NA | NA | NA | NA | 15286 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Du | NA | NA | NA | NA | 6879 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Du | NA | NA | NA | NA | 8825 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Duan | NA | NA | NA | NA | 4731 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Duan | NA | NA | NA | NA | 16104 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Fan | NA | NA | NA | NA | 6619 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Fan | NA | NA | NA | NA | 12402 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Fan | NA | NA | NA | NA | 12419 | NA | Pearl | NA | FALSE | FALSE | FALSE |
| Person | Li Fan | NA | NA | NA | NA | 16011 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Feng | NA | NA | NA | NA | 6282 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Feng | NA | NA | NA | NA | 8830 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Feng | NA | NA | NA | NA | 9047 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Fu | NA | NA | NA | NA | 1377 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Fu | NA | NA | NA | NA | 16088 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gao | NA | NA | NA | NA | 1232 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gao | NA | NA | NA | NA | 8809 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gao | NA | NA | NA | NA | 15487 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gong | NA | NA | NA | NA | 1093 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gong | NA | NA | NA | NA | 8306 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gong | NA | NA | NA | NA | 9121 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gong | NA | NA | NA | NA | 15523 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gong | NA | NA | NA | NA | 15589 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gu | NA | NA | NA | NA | 3447 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gu | NA | NA | NA | NA | 4247 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gu | NA | NA | NA | NA | 8398 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Gu | NA | NA | NA | NA | 16709 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Han | NA | NA | NA | NA | 9342 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Han | NA | NA | NA | NA | 11101 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li He | NA | NA | NA | NA | 1218 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li He | NA | NA | NA | NA | 4030 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li He | NA | NA | NA | NA | 13330 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li He | NA | NA | NA | NA | 13756 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li He | NA | NA | NA | NA | 16566 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Hou | NA | NA | NA | NA | 4417 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Hou | NA | NA | NA | NA | 6242 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Hu | NA | NA | NA | NA | 8725 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Hu | NA | NA | NA | NA | 10783 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Hu | NA | NA | NA | NA | 13876 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Hu | NA | NA | NA | NA | 15145 | NA | THA SAINT | NA | FALSE | FALSE | FALSE |
| Person | Li Hu | NA | NA | NA | NA | 16187 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Huang | NA | NA | NA | NA | 6550 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Huang | NA | NA | NA | NA | 7149 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Huang | NA | NA | NA | NA | 8126 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jia | NA | NA | NA | NA | 6441 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jia | NA | NA | NA | NA | 6517 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jia | NA | NA | NA | NA | 14006 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jia | NA | NA | NA | NA | 16332 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jiang | NA | NA | NA | NA | 3471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jiang | NA | NA | NA | NA | 9590 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jiang | NA | NA | NA | NA | 9674 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jin | NA | NA | NA | NA | 3841 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jin | NA | NA | NA | NA | 5978 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jin | NA | NA | NA | NA | 6712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jin | NA | NA | NA | NA | 12284 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Jin | NA | NA | NA | NA | 13792 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Kang | NA | NA | NA | NA | 6970 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Kang | NA | NA | NA | NA | 14073 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Kong | NA | NA | NA | NA | 853 | NA | Syntara | NA | FALSE | FALSE | FALSE |
| Person | Li Kong | NA | NA | NA | NA | 6223 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Kong | NA | NA | NA | NA | 15446 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lai | NA | NA | NA | NA | 13251 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lai | NA | NA | NA | NA | 16476 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lei | NA | NA | NA | NA | 507 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lei | NA | NA | NA | NA | 593 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lei | NA | NA | NA | NA | 10391 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lei | NA | NA | NA | NA | 12603 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lei | NA | NA | NA | NA | 13920 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Li | NA | NA | NA | NA | 6570 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Li | NA | NA | NA | NA | 12285 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liao | NA | NA | NA | NA | 313 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liao | NA | NA | NA | NA | 5235 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liao | NA | NA | NA | NA | 6308 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liao | NA | NA | NA | NA | 7542 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liao | NA | NA | NA | NA | 11804 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liao | NA | NA | NA | NA | 12716 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liao | NA | NA | NA | NA | 14641 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lin | NA | NA | NA | NA | 131 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lin | NA | NA | NA | NA | 12337 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lin | NA | NA | NA | NA | 13211 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lin | NA | NA | NA | NA | 13776 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liu | NA | NA | NA | NA | 2146 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Liu | NA | NA | NA | NA | 15050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Long | NA | NA | NA | NA | 7688 | NA | Desert Moon | NA | FALSE | FALSE | FALSE |
| Person | Li Long | NA | NA | NA | NA | 12374 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Long | NA | NA | NA | NA | 12960 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Long | NA | NA | NA | NA | 15172 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Long | NA | NA | NA | NA | 15725 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lu | NA | NA | NA | NA | 1858 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lu | NA | NA | NA | NA | 10340 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lu | NA | NA | NA | NA | 11589 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Lu | NA | NA | NA | NA | 13320 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Luo | NA | NA | NA | NA | 150 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Luo | NA | NA | NA | NA | 10031 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Luo | NA | NA | NA | NA | 15758 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ma | NA | NA | NA | NA | 1873 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ma | NA | NA | NA | NA | 2380 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ma | NA | NA | NA | NA | 12231 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ma | NA | NA | NA | NA | 12295 | NA | Myriad | NA | FALSE | FALSE | FALSE |
| Person | Li Mo | NA | NA | NA | NA | 178 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Mo | NA | NA | NA | NA | 659 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Mo | NA | NA | NA | NA | 13405 | NA | $PECTRUM | NA | FALSE | FALSE | FALSE |
| Person | Li Qian | NA | NA | NA | NA | 6828 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Qian | NA | NA | NA | NA | 10166 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Qiu | NA | NA | NA | NA | 1462 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Qiu | NA | NA | NA | NA | 6997 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ren | NA | NA | NA | NA | 9391 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ren | NA | NA | NA | NA | 9520 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ren | NA | NA | NA | NA | 13846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Ren | NA | NA | NA | NA | 15485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Shao | NA | NA | NA | NA | 1897 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Shao | NA | NA | NA | NA | 3214 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Shao | NA | NA | NA | NA | 8940 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Song | NA | NA | NA | NA | 5903 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Song | NA | NA | NA | NA | 6385 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Song | NA | NA | NA | NA | 7218 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Song | NA | NA | NA | NA | 13575 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Sun | NA | NA | NA | NA | 7220 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Sun | NA | NA | NA | NA | 11683 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tan | NA | NA | NA | NA | 5341 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tan | NA | NA | NA | NA | 11325 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tan | NA | NA | NA | NA | 13051 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tan | NA | NA | NA | NA | 15392 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tang | NA | NA | NA | NA | 3318 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tang | NA | NA | NA | NA | 9208 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tao | NA | NA | NA | NA | 10828 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tao | NA | NA | NA | NA | 13889 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tian | NA | NA | NA | NA | 3934 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tian | NA | NA | NA | NA | 6324 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Tian | NA | NA | NA | NA | 6964 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wan | NA | NA | NA | NA | 1014 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wan | NA | NA | NA | NA | 5503 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wan | NA | NA | NA | NA | 10985 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wan | NA | NA | NA | NA | 13550 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wei | NA | NA | NA | NA | 715 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wei | NA | NA | NA | NA | 9002 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wen | NA | NA | NA | NA | 5884 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wen | NA | NA | NA | NA | 6974 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wen | NA | NA | NA | NA | 11854 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wu | NA | NA | NA | NA | 1002 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Wu | NA | NA | NA | NA | 10250 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xia | NA | NA | NA | NA | 4812 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xia | NA | NA | NA | NA | 8500 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xia | NA | NA | NA | NA | 11090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xie | NA | NA | NA | NA | 274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xie | NA | NA | NA | NA | 12399 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xie | NA | NA | NA | NA | 12964 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xiong | NA | NA | NA | NA | 3783 | NA | Spectral Canticle | NA | FALSE | FALSE | FALSE |
| Person | Li Xiong | NA | NA | NA | NA | 9806 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xu | NA | NA | NA | NA | 12609 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xu | NA | NA | NA | NA | 14827 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xu | NA | NA | NA | NA | 15094 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xue | NA | NA | NA | NA | 3253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xue | NA | NA | NA | NA | 4462 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Xue | NA | NA | NA | NA | 7094 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yang | NA | NA | NA | NA | 1429 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yang | NA | NA | NA | NA | 2179 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yang | NA | NA | NA | NA | 6347 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yang | NA | NA | NA | NA | 8136 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yang | NA | NA | NA | NA | 11131 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yang | NA | NA | NA | NA | 15546 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yao | NA | NA | NA | NA | 9024 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yao | NA | NA | NA | NA | 13725 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yi | NA | NA | NA | NA | 13 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yi | NA | NA | NA | NA | 2900 | NA | Quinn Atlas | NA | FALSE | FALSE | FALSE |
| Person | Li Yi | NA | NA | NA | NA | 7163 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yin | NA | NA | NA | NA | 7192 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yin | NA | NA | NA | NA | 7819 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yin | NA | NA | NA | NA | 8378 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yuan | NA | NA | NA | NA | 13370 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Yuan | NA | NA | NA | NA | 13596 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zeng | NA | NA | NA | NA | 3645 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zeng | NA | NA | NA | NA | 7852 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zeng | NA | NA | NA | NA | 16583 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zheng | NA | NA | NA | NA | 353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zheng | NA | NA | NA | NA | 2305 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zheng | NA | NA | NA | NA | 3077 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zheng | NA | NA | NA | NA | 8317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zheng | NA | NA | NA | NA | 10531 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zhou | NA | NA | NA | NA | 1727 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zhou | NA | NA | NA | NA | 8980 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zhou | NA | NA | NA | NA | 12935 | NA | Aiden Cole | NA | FALSE | FALSE | FALSE |
| Person | Li Zhou | NA | NA | NA | NA | 14070 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zhu | NA | NA | NA | NA | 10634 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zhu | NA | NA | NA | NA | 15586 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zou | NA | NA | NA | NA | 3829 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Li Zou | NA | NA | NA | NA | 7629 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Linda Reed | NA | NA | NA | NA | 2746 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Linda Reed | NA | NA | NA | NA | 11983 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lisa Jones | NA | NA | NA | NA | 3968 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lisa Jones | NA | NA | NA | NA | 5954 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lisa Lopez | NA | NA | NA | NA | 7471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lisa Lopez | NA | NA | NA | NA | 14234 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lisa Martin | NA | NA | NA | NA | 2171 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Lisa Martin | NA | NA | NA | NA | 12798 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Little Pine Records | NA | NA | NA | NA | 1339 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Little Pine Records | NA | NA | NA | NA | 17387 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | MTJ Horizon | NA | NA | NA | NA | 704 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | MTJ Horizon | NA | NA | NA | NA | 17376 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Matthew Brown | NA | NA | NA | NA | 5686 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Matthew Brown | NA | NA | NA | NA | 6933 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Matthew Moss | NA | NA | NA | NA | 989 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Matthew Moss | NA | NA | NA | NA | 16480 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Matthew Smith | NA | NA | NA | NA | 11123 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Matthew Smith | NA | NA | NA | NA | 13767 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Medoc Music | NA | NA | NA | NA | 1134 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Medoc Music | NA | NA | NA | NA | 17383 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Melissa Smith | NA | NA | NA | NA | 2245 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Melissa Smith | NA | NA | NA | NA | 15676 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Aguilar | NA | NA | NA | NA | 3550 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Aguilar | NA | NA | NA | NA | 10991 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Gomez | NA | NA | NA | NA | 9078 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Gomez | NA | NA | NA | NA | 14685 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Harris | NA | NA | NA | NA | 13605 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Harris | NA | NA | NA | NA | 16984 | NA | Axel Blaze | NA | FALSE | FALSE | FALSE |
| Person | Michael Jones | NA | NA | NA | NA | 13549 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Jones | NA | NA | NA | NA | 14265 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Moore | NA | NA | NA | NA | 7301 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Moore | NA | NA | NA | NA | 12459 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Pratt | NA | NA | NA | NA | 4128 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Pratt | NA | NA | NA | NA | 7506 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Price | NA | NA | NA | NA | 9338 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Price | NA | NA | NA | NA | 11069 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Smith | NA | NA | NA | NA | 5763 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Smith | NA | NA | NA | NA | 7363 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michael Smith | NA | NA | NA | NA | 16344 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michelle Davis | NA | NA | NA | NA | 2866 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michelle Davis | NA | NA | NA | NA | 4495 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michelle Davis | NA | NA | NA | NA | 12197 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michelle Ellis | NA | NA | NA | NA | 5192 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michelle Ellis | NA | NA | NA | NA | 14978 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michelle Williams | NA | NA | NA | NA | 1143 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Michelle Williams | NA | NA | NA | NA | 12800 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Miki Hayashi | NA | NA | NA | NA | 99 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Miki Hayashi | NA | NA | NA | NA | 8437 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Bai | NA | NA | NA | NA | 6430 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Bai | NA | NA | NA | NA | 15694 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Cai | NA | NA | NA | NA | 2876 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Cai | NA | NA | NA | NA | 12269 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Chang | NA | NA | NA | NA | 396 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Chang | NA | NA | NA | NA | 643 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Chang | NA | NA | NA | NA | 2697 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Chang | NA | NA | NA | NA | 13277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Chen | NA | NA | NA | NA | 3938 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Chen | NA | NA | NA | NA | 4218 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Chen | NA | NA | NA | NA | 5156 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Chen | NA | NA | NA | NA | 11647 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Cheng | NA | NA | NA | NA | 11088 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Cheng | NA | NA | NA | NA | 11476 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Cui | NA | NA | NA | NA | 3825 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Cui | NA | NA | NA | NA | 8302 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Cui | NA | NA | NA | NA | 10261 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Cui | NA | NA | NA | NA | 12864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Dai | NA | NA | NA | NA | 3293 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Dai | NA | NA | NA | NA | 4766 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Dai | NA | NA | NA | NA | 15914 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Deng | NA | NA | NA | NA | 2352 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Deng | NA | NA | NA | NA | 6018 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Deng | NA | NA | NA | NA | 7805 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Deng | NA | NA | NA | NA | 11982 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Deng | NA | NA | NA | NA | 14790 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ding | NA | NA | NA | NA | 8779 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ding | NA | NA | NA | NA | 15648 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Duan | NA | NA | NA | NA | 904 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Duan | NA | NA | NA | NA | 1303 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Duan | NA | NA | NA | NA | 2295 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Duan | NA | NA | NA | NA | 8619 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Duan | NA | NA | NA | NA | 8664 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Duan | NA | NA | NA | NA | 11498 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Fan | NA | NA | NA | NA | 1726 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Fan | NA | NA | NA | NA | 8390 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Fan | NA | NA | NA | NA | 10177 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Fu | NA | NA | NA | NA | 2850 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Fu | NA | NA | NA | NA | 7060 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Fu | NA | NA | NA | NA | 9794 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Gao | NA | NA | NA | NA | 3078 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Gao | NA | NA | NA | NA | 4767 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Gao | NA | NA | NA | NA | 5500 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Gao | NA | NA | NA | NA | 13290 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Gu | NA | NA | NA | NA | 2105 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Gu | NA | NA | NA | NA | 11250 | NA | The Glitch Monarch | NA | FALSE | FALSE | FALSE |
| Person | Min Guo | NA | NA | NA | NA | 2609 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Guo | NA | NA | NA | NA | 14195 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Guo | NA | NA | NA | NA | 14836 | NA | PH∆SE | NA | FALSE | FALSE | FALSE |
| Person | Min Guo | NA | NA | NA | NA | 16195 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min He | NA | NA | NA | NA | 5038 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min He | NA | NA | NA | NA | 6996 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min He | NA | NA | NA | NA | 7915 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Hou | NA | NA | NA | NA | 4470 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Hou | NA | NA | NA | NA | 5662 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Hou | NA | NA | NA | NA | 11167 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Hou | NA | NA | NA | NA | 16177 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Huang | NA | NA | NA | NA | 5731 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Huang | NA | NA | NA | NA | 8379 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Huang | NA | NA | NA | NA | 8626 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Huang | NA | NA | NA | NA | 12288 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jia | NA | NA | NA | NA | 1664 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jia | NA | NA | NA | NA | 10034 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jia | NA | NA | NA | NA | 13793 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jiang | NA | NA | NA | NA | 3527 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jiang | NA | NA | NA | NA | 4743 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jiang | NA | NA | NA | NA | 4768 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jiang | NA | NA | NA | NA | 12329 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jiang | NA | NA | NA | NA | 15868 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jin | NA | NA | NA | NA | 394 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jin | NA | NA | NA | NA | 3070 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jin | NA | NA | NA | NA | 3521 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jin | NA | NA | NA | NA | 3680 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jin | NA | NA | NA | NA | 7411 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jin | NA | NA | NA | NA | 7610 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Jin | NA | NA | NA | NA | 15154 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Kong | NA | NA | NA | NA | 1225 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Kong | NA | NA | NA | NA | 1277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Kong | NA | NA | NA | NA | 7217 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Kong | NA | NA | NA | NA | 14751 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Kong | NA | NA | NA | NA | 16671 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lei | NA | NA | NA | NA | 1519 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lei | NA | NA | NA | NA | 2966 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lei | NA | NA | NA | NA | 4196 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lei | NA | NA | NA | NA | 6547 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lei | NA | NA | NA | NA | 6877 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lei | NA | NA | NA | NA | 7906 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lei | NA | NA | NA | NA | 9478 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lei | NA | NA | NA | NA | 12247 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Li | NA | NA | NA | NA | 2980 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Li | NA | NA | NA | NA | 5091 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Li | NA | NA | NA | NA | 8672 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liang | NA | NA | NA | NA | 5207 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liang | NA | NA | NA | NA | 11478 | NA | Tyler Sage | NA | FALSE | FALSE | FALSE |
| Person | Min Liang | NA | NA | NA | NA | 13439 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liang | NA | NA | NA | NA | 16414 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liao | NA | NA | NA | NA | 657 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liao | NA | NA | NA | NA | 2255 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liao | NA | NA | NA | NA | 3518 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liao | NA | NA | NA | NA | 8370 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liao | NA | NA | NA | NA | 9323 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liao | NA | NA | NA | NA | 15351 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lin | NA | NA | NA | NA | 2090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Lin | NA | NA | NA | NA | 14412 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liu | NA | NA | NA | NA | 8642 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Liu | NA | NA | NA | NA | 9946 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Long | NA | NA | NA | NA | 310 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Long | NA | NA | NA | NA | 3202 | NA | Resonance | NA | FALSE | FALSE | FALSE |
| Person | Min Long | NA | NA | NA | NA | 3760 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Long | NA | NA | NA | NA | 4709 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Long | NA | NA | NA | NA | 15707 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ma | NA | NA | NA | NA | 861 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ma | NA | NA | NA | NA | 6544 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Meng | NA | NA | NA | NA | 6283 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Meng | NA | NA | NA | NA | 9629 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Mo | NA | NA | NA | NA | 5511 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Mo | NA | NA | NA | NA | 8140 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Mo | NA | NA | NA | NA | 10193 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Mo | NA | NA | NA | NA | 10639 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Pan | NA | NA | NA | NA | 140 | NA | Oblivion Rhapsody | NA | FALSE | FALSE | FALSE |
| Person | Min Pan | NA | NA | NA | NA | 16222 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Peng | NA | NA | NA | NA | 1911 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Peng | NA | NA | NA | NA | 5263 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Peng | NA | NA | NA | NA | 10048 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qian | NA | NA | NA | NA | 5772 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qian | NA | NA | NA | NA | 5904 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qian | NA | NA | NA | NA | 5984 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qian | NA | NA | NA | NA | 8808 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qiao | NA | NA | NA | NA | 63 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qiao | NA | NA | NA | NA | 14148 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qin | NA | NA | NA | NA | 2 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qin | NA | NA | NA | NA | 2414 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qin | NA | NA | NA | NA | 8499 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qin | NA | NA | NA | NA | 9594 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qin | NA | NA | NA | NA | 12859 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qin | NA | NA | NA | NA | 13153 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qin | NA | NA | NA | NA | 14470 | NA | Crystal Dove | NA | FALSE | FALSE | FALSE |
| Person | Min Qiu | NA | NA | NA | NA | 2587 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qiu | NA | NA | NA | NA | 3943 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qiu | NA | NA | NA | NA | 5185 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Qiu | NA | NA | NA | NA | 15951 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ren | NA | NA | NA | NA | 2853 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ren | NA | NA | NA | NA | 6239 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ren | NA | NA | NA | NA | 7899 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ren | NA | NA | NA | NA | 13194 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shao | NA | NA | NA | NA | 6758 | NA | Radio Seraph | NA | FALSE | FALSE | FALSE |
| Person | Min Shao | NA | NA | NA | NA | 6807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shao | NA | NA | NA | NA | 8369 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shen | NA | NA | NA | NA | 3389 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shen | NA | NA | NA | NA | 9673 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shi | NA | NA | NA | NA | 1164 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shi | NA | NA | NA | NA | 6648 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shi | NA | NA | NA | NA | 9682 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shi | NA | NA | NA | NA | 9819 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Shi | NA | NA | NA | NA | 11055 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Su | NA | NA | NA | NA | 6652 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Su | NA | NA | NA | NA | 10822 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Sun | NA | NA | NA | NA | 2597 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Sun | NA | NA | NA | NA | 6487 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Sun | NA | NA | NA | NA | 7998 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Sun | NA | NA | NA | NA | 12660 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Tan | NA | NA | NA | NA | 2482 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Tan | NA | NA | NA | NA | 8577 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Tao | NA | NA | NA | NA | 909 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Tao | NA | NA | NA | NA | 4005 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Tao | NA | NA | NA | NA | 12090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Tian | NA | NA | NA | NA | 1784 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Tian | NA | NA | NA | NA | 12141 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wan | NA | NA | NA | NA | 2547 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wan | NA | NA | NA | NA | 7293 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wan | NA | NA | NA | NA | 15109 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wang | NA | NA | NA | NA | 6419 | NA | The Ember Syndicate | NA | FALSE | FALSE | FALSE |
| Person | Min Wang | NA | NA | NA | NA | 7811 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wang | NA | NA | NA | NA | 12664 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wen | NA | NA | NA | NA | 1910 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wen | NA | NA | NA | NA | 10914 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wu | NA | NA | NA | NA | 7260 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wu | NA | NA | NA | NA | 9381 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Wu | NA | NA | NA | NA | 14434 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xia | NA | NA | NA | NA | 10429 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xia | NA | NA | NA | NA | 13242 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xia | NA | NA | NA | NA | 16050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiang | NA | NA | NA | NA | 3658 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiang | NA | NA | NA | NA | 5378 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiang | NA | NA | NA | NA | 6850 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiang | NA | NA | NA | NA | 8161 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiang | NA | NA | NA | NA | 15870 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xie | NA | NA | NA | NA | 658 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xie | NA | NA | NA | NA | 7057 | NA | J.R. Vale | NA | FALSE | FALSE | FALSE |
| Person | Min Xie | NA | NA | NA | NA | 7486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiong | NA | NA | NA | NA | 5512 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiong | NA | NA | NA | NA | 6195 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiong | NA | NA | NA | NA | 7199 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xiong | NA | NA | NA | NA | 15956 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xu | NA | NA | NA | NA | 12251 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xu | NA | NA | NA | NA | 15329 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xue | NA | NA | NA | NA | 2157 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Xue | NA | NA | NA | NA | 4039 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yan | NA | NA | NA | NA | 588 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yan | NA | NA | NA | NA | 6943 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yao | NA | NA | NA | NA | 5623 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yao | NA | NA | NA | NA | 11343 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yao | NA | NA | NA | NA | 12736 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ye | NA | NA | NA | NA | 82 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Ye | NA | NA | NA | NA | 8232 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yi | NA | NA | NA | NA | 4083 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yi | NA | NA | NA | NA | 16294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yin | NA | NA | NA | NA | 11943 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yin | NA | NA | NA | NA | 12510 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yu | NA | NA | NA | NA | 2158 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yu | NA | NA | NA | NA | 3685 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yu | NA | NA | NA | NA | 8143 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yu | NA | NA | NA | NA | 12683 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yu | NA | NA | NA | NA | 15943 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yuan | NA | NA | NA | NA | 3612 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Yuan | NA | NA | NA | NA | 8326 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zeng | NA | NA | NA | NA | 4635 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zeng | NA | NA | NA | NA | 11367 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhang | NA | NA | NA | NA | 8374 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhang | NA | NA | NA | NA | 16548 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhao | NA | NA | NA | NA | 3161 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhao | NA | NA | NA | NA | 5481 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhao | NA | NA | NA | NA | 11845 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhao | NA | NA | NA | NA | 11963 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhao | NA | NA | NA | NA | 14846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhao | NA | NA | NA | NA | 16049 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zheng | NA | NA | NA | NA | 7921 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zheng | NA | NA | NA | NA | 9730 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhong | NA | NA | NA | NA | 6188 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhong | NA | NA | NA | NA | 16651 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhou | NA | NA | NA | NA | 484 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhou | NA | NA | NA | NA | 12911 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhou | NA | NA | NA | NA | 14704 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zhou | NA | NA | NA | NA | 15558 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zou | NA | NA | NA | NA | 902 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zou | NA | NA | NA | NA | 9139 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zou | NA | NA | NA | NA | 9324 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Min Zou | NA | NA | NA | NA | 12618 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Bai | NA | NA | NA | NA | 1281 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Bai | NA | NA | NA | NA | 4625 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cao | NA | NA | NA | NA | 3694 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cao | NA | NA | NA | NA | 7678 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cao | NA | NA | NA | NA | 10041 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cao | NA | NA | NA | NA | 11151 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chang | NA | NA | NA | NA | 2349 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chang | NA | NA | NA | NA | 11750 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chang | NA | NA | NA | NA | 15013 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chen | NA | NA | NA | NA | 929 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chen | NA | NA | NA | NA | 5495 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chen | NA | NA | NA | NA | 7225 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chen | NA | NA | NA | NA | 8410 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chen | NA | NA | NA | NA | 9699 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Chen | NA | NA | NA | NA | 13305 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cheng | NA | NA | NA | NA | 1003 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cheng | NA | NA | NA | NA | 3269 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cheng | NA | NA | NA | NA | 6457 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cheng | NA | NA | NA | NA | 13604 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cheng | NA | NA | NA | NA | 16538 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cui | NA | NA | NA | NA | 7684 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cui | NA | NA | NA | NA | 8746 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cui | NA | NA | NA | NA | 11690 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cui | NA | NA | NA | NA | 11764 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Cui | NA | NA | NA | NA | 15166 | NA | Bishop VII | NA | FALSE | FALSE | FALSE |
| Person | Ming Dai | NA | NA | NA | NA | 1876 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Dai | NA | NA | NA | NA | 3227 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Dai | NA | NA | NA | NA | 4329 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Dai | NA | NA | NA | NA | 9845 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Dai | NA | NA | NA | NA | 10665 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Deng | NA | NA | NA | NA | 10545 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Deng | NA | NA | NA | NA | 16138 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Ding | NA | NA | NA | NA | 2457 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Ding | NA | NA | NA | NA | 4256 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Ding | NA | NA | NA | NA | 11752 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Ding | NA | NA | NA | NA | 14712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Ding | NA | NA | NA | NA | 14905 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Du | NA | NA | NA | NA | 7877 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Du | NA | NA | NA | NA | 9293 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Du | NA | NA | NA | NA | 11192 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Duan | NA | NA | NA | NA | 10705 | NA | Nova Apparition | NA | FALSE | FALSE | FALSE |
| Person | Ming Duan | NA | NA | NA | NA | 12144 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Duan | NA | NA | NA | NA | 14988 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Duan | NA | NA | NA | NA | 15269 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Duan | NA | NA | NA | NA | 15923 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Fan | NA | NA | NA | NA | 5791 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Fan | NA | NA | NA | NA | 6091 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Fan | NA | NA | NA | NA | 9386 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Fan | NA | NA | NA | NA | 10425 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Fang | NA | NA | NA | NA | 3453 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Fang | NA | NA | NA | NA | 5158 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Fang | NA | NA | NA | NA | 7910 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Feng | NA | NA | NA | NA | 5274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Feng | NA | NA | NA | NA | 13252 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Gu | NA | NA | NA | NA | 824 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Gu | NA | NA | NA | NA | 952 | NA | BLVCK MOON | NA | FALSE | FALSE | FALSE |
| Person | Ming Han | NA | NA | NA | NA | 4813 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Han | NA | NA | NA | NA | 8465 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Hao | NA | NA | NA | NA | 9487 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Hao | NA | NA | NA | NA | 10757 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming He | NA | NA | NA | NA | 1696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming He | NA | NA | NA | NA | 6197 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming He | NA | NA | NA | NA | 6806 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming He | NA | NA | NA | NA | 10076 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming He | NA | NA | NA | NA | 12107 | NA | Solstice Monologue | NA | FALSE | FALSE | FALSE |
| Person | Ming Hou | NA | NA | NA | NA | 13769 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Hou | NA | NA | NA | NA | 14810 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Hou | NA | NA | NA | NA | 15097 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Hu | NA | NA | NA | NA | 4082 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Hu | NA | NA | NA | NA | 6878 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Hu | NA | NA | NA | NA | 8131 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Hu | NA | NA | NA | NA | 8146 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Huang | NA | NA | NA | NA | 3990 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Huang | NA | NA | NA | NA | 6334 | NA | Dom Rivers | NA | FALSE | FALSE | FALSE |
| Person | Ming Huang | NA | NA | NA | NA | 7117 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Huang | NA | NA | NA | NA | 10527 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Jia | NA | NA | NA | NA | 2882 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Jia | NA | NA | NA | NA | 4174 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Jia | NA | NA | NA | NA | 9213 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Jiang | NA | NA | NA | NA | 4729 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Jiang | NA | NA | NA | NA | 6413 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Jiang | NA | NA | NA | NA | 8133 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Jiang | NA | NA | NA | NA | 16052 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Kang | NA | NA | NA | NA | 2468 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Kang | NA | NA | NA | NA | 10178 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Kang | NA | NA | NA | NA | 14973 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Kong | NA | NA | NA | NA | 8514 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Kong | NA | NA | NA | NA | 14775 | NA | L.A. Rose | NA | FALSE | FALSE | FALSE |
| Person | Ming Kong | NA | NA | NA | NA | 14955 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lai | NA | NA | NA | NA | 1909 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lai | NA | NA | NA | NA | 3279 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lai | NA | NA | NA | NA | 8774 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lei | NA | NA | NA | NA | 6488 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lei | NA | NA | NA | NA | 12398 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lei | NA | NA | NA | NA | 14055 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lei | NA | NA | NA | NA | 14974 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Li | NA | NA | NA | NA | 3231 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Li | NA | NA | NA | NA | 7847 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Li | NA | NA | NA | NA | 9170 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Liang | NA | NA | NA | NA | 4318 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Liang | NA | NA | NA | NA | 15411 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lin | NA | NA | NA | NA | 8864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Lin | NA | NA | NA | NA | 16387 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Long | NA | NA | NA | NA | 1335 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Long | NA | NA | NA | NA | 3494 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Long | NA | NA | NA | NA | 4806 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Long | NA | NA | NA | NA | 10243 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Luo | NA | NA | NA | NA | 4712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Luo | NA | NA | NA | NA | 7115 | NA | Z-LO THE MYST | NA | FALSE | FALSE | FALSE |
| Person | Ming Luo | NA | NA | NA | NA | 11944 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Mao | NA | NA | NA | NA | 4248 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Mao | NA | NA | NA | NA | 8388 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Mao | NA | NA | NA | NA | 9813 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Mao | NA | NA | NA | NA | 13694 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Pan | NA | NA | NA | NA | 6459 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Pan | NA | NA | NA | NA | 13159 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qian | NA | NA | NA | NA | 3473 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qian | NA | NA | NA | NA | 3671 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qiao | NA | NA | NA | NA | 3377 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qiao | NA | NA | NA | NA | 6431 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qiao | NA | NA | NA | NA | 7917 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qiao | NA | NA | NA | NA | 14297 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qiu | NA | NA | NA | NA | 5486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qiu | NA | NA | NA | NA | 11560 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qiu | NA | NA | NA | NA | 13174 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Qiu | NA | NA | NA | NA | 14472 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Ren | NA | NA | NA | NA | 76 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Ren | NA | NA | NA | NA | 6226 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Shao | NA | NA | NA | NA | 7814 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Shao | NA | NA | NA | NA | 10334 | NA | Terra | NA | FALSE | FALSE | FALSE |
| Person | Ming Shao | NA | NA | NA | NA | 15720 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Shen | NA | NA | NA | NA | 6104 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Shen | NA | NA | NA | NA | 8046 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Shen | NA | NA | NA | NA | 15794 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Shi | NA | NA | NA | NA | 10362 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Shi | NA | NA | NA | NA | 12746 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Song | NA | NA | NA | NA | 1864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Song | NA | NA | NA | NA | 10984 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Song | NA | NA | NA | NA | 13594 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Su | NA | NA | NA | NA | 6527 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Su | NA | NA | NA | NA | 7203 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Sun | NA | NA | NA | NA | 828 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Sun | NA | NA | NA | NA | 5715 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Sun | NA | NA | NA | NA | 7146 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Sun | NA | NA | NA | NA | 8654 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Sun | NA | NA | NA | NA | 11150 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Sun | NA | NA | NA | NA | 16066 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Tian | NA | NA | NA | NA | 3657 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Tian | NA | NA | NA | NA | 4320 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Wan | NA | NA | NA | NA | 3731 | NA | Echo Dominion | NA | FALSE | FALSE | FALSE |
| Person | Ming Wan | NA | NA | NA | NA | 8322 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Wan | NA | NA | NA | NA | 14005 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Wang | NA | NA | NA | NA | 7932 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Wang | NA | NA | NA | NA | 9898 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Wang | NA | NA | NA | NA | 16265 | NA | Sky | NA | FALSE | FALSE | FALSE |
| Person | Ming Wei | NA | NA | NA | NA | 6084 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Wei | NA | NA | NA | NA | 15780 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xia | NA | NA | NA | NA | 10901 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xia | NA | NA | NA | NA | 12849 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xia | NA | NA | NA | NA | 13686 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiang | NA | NA | NA | NA | 194 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiang | NA | NA | NA | NA | 7143 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiang | NA | NA | NA | NA | 14122 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiang | NA | NA | NA | NA | 14415 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiang | NA | NA | NA | NA | 16266 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiao | NA | NA | NA | NA | 688 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiao | NA | NA | NA | NA | 8047 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiao | NA | NA | NA | NA | 11338 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xie | NA | NA | NA | NA | 13827 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xie | NA | NA | NA | NA | 15878 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiong | NA | NA | NA | NA | 3430 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiong | NA | NA | NA | NA | 11027 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xiong | NA | NA | NA | NA | 11291 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xu | NA | NA | NA | NA | 7487 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xu | NA | NA | NA | NA | 15412 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xu | NA | NA | NA | NA | 16634 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xue | NA | NA | NA | NA | 1302 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Xue | NA | NA | NA | NA | 15262 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yan | NA | NA | NA | NA | 639 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yan | NA | NA | NA | NA | 937 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yang | NA | NA | NA | NA | 2274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yang | NA | NA | NA | NA | 3933 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yang | NA | NA | NA | NA | 9343 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yang | NA | NA | NA | NA | 11638 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yang | NA | NA | NA | NA | 12394 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yao | NA | NA | NA | NA | 1318 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yao | NA | NA | NA | NA | 2645 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yao | NA | NA | NA | NA | 7021 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yao | NA | NA | NA | NA | 11988 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yao | NA | NA | NA | NA | 12062 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yao | NA | NA | NA | NA | 12302 | NA | Indigo Storm | NA | FALSE | FALSE | FALSE |
| Person | Ming Yu | NA | NA | NA | NA | 6945 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yu | NA | NA | NA | NA | 13177 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yuan | NA | NA | NA | NA | 7500 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yuan | NA | NA | NA | NA | 7717 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Yuan | NA | NA | NA | NA | 14931 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zeng | NA | NA | NA | NA | 5418 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zeng | NA | NA | NA | NA | 14413 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhao | NA | NA | NA | NA | 978 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhao | NA | NA | NA | NA | 3544 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhao | NA | NA | NA | NA | 3698 | NA | FVDE | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhao | NA | NA | NA | NA | 13241 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zheng | NA | NA | NA | NA | 5529 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zheng | NA | NA | NA | NA | 6269 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zheng | NA | NA | NA | NA | 13136 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhong | NA | NA | NA | NA | 10637 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhong | NA | NA | NA | NA | 13950 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhou | NA | NA | NA | NA | 4654 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhou | NA | NA | NA | NA | 5261 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhou | NA | NA | NA | NA | 6335 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhou | NA | NA | NA | NA | 11245 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhou | NA | NA | NA | NA | 11372 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhou | NA | NA | NA | NA | 15051 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhou | NA | NA | NA | NA | 15416 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zhou | NA | NA | NA | NA | 15856 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zou | NA | NA | NA | NA | 2098 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ming Zou | NA | NA | NA | NA | 6221 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Monica Brown | NA | NA | NA | NA | 2389 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Monica Brown | NA | NA | NA | NA | 15901 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Bai | NA | NA | NA | NA | 7807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Bai | NA | NA | NA | NA | 10255 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Bai | NA | NA | NA | NA | 16080 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Cai | NA | NA | NA | NA | 7025 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Cai | NA | NA | NA | NA | 15919 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Cao | NA | NA | NA | NA | 3330 | NA | Jay Carter | NA | FALSE | FALSE | FALSE |
| Person | Na Cao | NA | NA | NA | NA | 6093 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Chang | NA | NA | NA | NA | 4424 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Chang | NA | NA | NA | NA | 15096 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Chang | NA | NA | NA | NA | 15208 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Chen | NA | NA | NA | NA | 4330 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Chen | NA | NA | NA | NA | 12850 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Chen | NA | NA | NA | NA | 14981 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Chen | NA | NA | NA | NA | 15266 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Cui | NA | NA | NA | NA | 5092 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Cui | NA | NA | NA | NA | 7245 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Cui | NA | NA | NA | NA | 7329 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Cui | NA | NA | NA | NA | 10930 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Cui | NA | NA | NA | NA | 15107 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dai | NA | NA | NA | NA | 5380 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dai | NA | NA | NA | NA | 7429 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dai | NA | NA | NA | NA | 8600 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dai | NA | NA | NA | NA | 12526 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Deng | NA | NA | NA | NA | 2001 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Deng | NA | NA | NA | NA | 9949 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Deng | NA | NA | NA | NA | 15033 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dong | NA | NA | NA | NA | 40 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dong | NA | NA | NA | NA | 2912 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dong | NA | NA | NA | NA | 6653 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dong | NA | NA | NA | NA | 6814 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dong | NA | NA | NA | NA | 8670 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dong | NA | NA | NA | NA | 13401 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Dong | NA | NA | NA | NA | 13801 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Duan | NA | NA | NA | NA | 1803 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Duan | NA | NA | NA | NA | 9439 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Fan | NA | NA | NA | NA | 594 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Fan | NA | NA | NA | NA | 6437 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Feng | NA | NA | NA | NA | 4301 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Feng | NA | NA | NA | NA | 10389 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Feng | NA | NA | NA | NA | 15872 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Fu | NA | NA | NA | NA | 5474 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Fu | NA | NA | NA | NA | 16468 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Gao | NA | NA | NA | NA | 228 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Gao | NA | NA | NA | NA | 3492 | NA | The Hollow Manuscript | NA | FALSE | FALSE | FALSE |
| Person | Na Gu | NA | NA | NA | NA | 4197 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Gu | NA | NA | NA | NA | 5924 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Gu | NA | NA | NA | NA | 9316 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Gu | NA | NA | NA | NA | 10253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Guo | NA | NA | NA | NA | 52 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Guo | NA | NA | NA | NA | 7973 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Guo | NA | NA | NA | NA | 16730 | NA | Jenna Sky | NA | FALSE | FALSE | FALSE |
| Person | Na Han | NA | NA | NA | NA | 6174 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Han | NA | NA | NA | NA | 6621 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Han | NA | NA | NA | NA | 12748 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Hou | NA | NA | NA | NA | 11727 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Hou | NA | NA | NA | NA | 13500 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Hou | NA | NA | NA | NA | 15511 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Hu | NA | NA | NA | NA | 373 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Hu | NA | NA | NA | NA | 538 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Jia | NA | NA | NA | NA | 2219 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Jia | NA | NA | NA | NA | 7791 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Jia | NA | NA | NA | NA | 9821 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Jin | NA | NA | NA | NA | 5850 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Jin | NA | NA | NA | NA | 6292 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Jin | NA | NA | NA | NA | 13329 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Kang | NA | NA | NA | NA | 268 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Kang | NA | NA | NA | NA | 2456 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Kong | NA | NA | NA | NA | 5005 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Kong | NA | NA | NA | NA | 7178 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Kong | NA | NA | NA | NA | 13879 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Kong | NA | NA | NA | NA | 15698 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Kong | NA | NA | NA | NA | 16439 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Lai | NA | NA | NA | NA | 275 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Lai | NA | NA | NA | NA | 2050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Lai | NA | NA | NA | NA | 3654 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Li | NA | NA | NA | NA | 2051 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Li | NA | NA | NA | NA | 3647 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Li | NA | NA | NA | NA | 6847 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Li | NA | NA | NA | NA | 13440 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Liao | NA | NA | NA | NA | 3066 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Liao | NA | NA | NA | NA | 6085 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Liao | NA | NA | NA | NA | 12129 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Lu | NA | NA | NA | NA | 3398 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Lu | NA | NA | NA | NA | 4544 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Luo | NA | NA | NA | NA | 5359 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Luo | NA | NA | NA | NA | 13706 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ma | NA | NA | NA | NA | 3824 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ma | NA | NA | NA | NA | 3958 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ma | NA | NA | NA | NA | 12026 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Mao | NA | NA | NA | NA | 2507 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Mao | NA | NA | NA | NA | 15795 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Meng | NA | NA | NA | NA | 1765 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Meng | NA | NA | NA | NA | 8947 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Meng | NA | NA | NA | NA | 11976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Mo | NA | NA | NA | NA | 2088 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Mo | NA | NA | NA | NA | 3638 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Pan | NA | NA | NA | NA | 649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Pan | NA | NA | NA | NA | 1196 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Peng | NA | NA | NA | NA | 955 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Peng | NA | NA | NA | NA | 1866 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Peng | NA | NA | NA | NA | 6458 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Peng | NA | NA | NA | NA | 15942 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Peng | NA | NA | NA | NA | 16732 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qian | NA | NA | NA | NA | 147 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qian | NA | NA | NA | NA | 3036 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qian | NA | NA | NA | NA | 3314 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qian | NA | NA | NA | NA | 3317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qian | NA | NA | NA | NA | 6819 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qin | NA | NA | NA | NA | 10335 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qin | NA | NA | NA | NA | 12950 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qin | NA | NA | NA | NA | 13892 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qiu | NA | NA | NA | NA | 4310 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Qiu | NA | NA | NA | NA | 12900 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ren | NA | NA | NA | NA | 3198 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ren | NA | NA | NA | NA | 4050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ren | NA | NA | NA | NA | 4185 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ren | NA | NA | NA | NA | 4398 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ren | NA | NA | NA | NA | 12929 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ren | NA | NA | NA | NA | 13962 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Shao | NA | NA | NA | NA | 754 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Shao | NA | NA | NA | NA | 4460 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Shao | NA | NA | NA | NA | 10547 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Shao | NA | NA | NA | NA | 13311 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Shao | NA | NA | NA | NA | 15171 | NA | Merit | NA | FALSE | FALSE | FALSE |
| Person | Na Song | NA | NA | NA | NA | 3059 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Song | NA | NA | NA | NA | 13253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Song | NA | NA | NA | NA | 16128 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Su | NA | NA | NA | NA | 2750 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Su | NA | NA | NA | NA | 5770 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Su | NA | NA | NA | NA | 7871 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Su | NA | NA | NA | NA | 8386 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Tan | NA | NA | NA | NA | 6096 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Tan | NA | NA | NA | NA | 6876 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Tian | NA | NA | NA | NA | 8452 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Tian | NA | NA | NA | NA | 14737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wei | NA | NA | NA | NA | 5661 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wei | NA | NA | NA | NA | 6290 | NA | Neon Oracle | NA | FALSE | FALSE | FALSE |
| Person | Na Wei | NA | NA | NA | NA | 11818 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wei | NA | NA | NA | NA | 15353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wen | NA | NA | NA | NA | 8895 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wen | NA | NA | NA | NA | 9703 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wen | NA | NA | NA | NA | 9915 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wen | NA | NA | NA | NA | 10087 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wu | NA | NA | NA | NA | 737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wu | NA | NA | NA | NA | 927 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Wu | NA | NA | NA | NA | 4811 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Xiang | NA | NA | NA | NA | 16077 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Xiang | NA | NA | NA | NA | 16288 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Xie | NA | NA | NA | NA | 5024 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Xie | NA | NA | NA | NA | 15509 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Xu | NA | NA | NA | NA | 6553 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Xu | NA | NA | NA | NA | 13466 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yan | NA | NA | NA | NA | 1078 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yan | NA | NA | NA | NA | 6212 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yan | NA | NA | NA | NA | 6552 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yang | NA | NA | NA | NA | 2501 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yang | NA | NA | NA | NA | 5105 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yang | NA | NA | NA | NA | 9063 | NA | Solar Drift | NA | FALSE | FALSE | FALSE |
| Person | Na Yang | NA | NA | NA | NA | 11282 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yao | NA | NA | NA | NA | 941 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yao | NA | NA | NA | NA | 3331 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ye | NA | NA | NA | NA | 5209 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Ye | NA | NA | NA | NA | 14298 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yi | NA | NA | NA | NA | 2685 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yi | NA | NA | NA | NA | 6795 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yi | NA | NA | NA | NA | 13444 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yin | NA | NA | NA | NA | 864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yin | NA | NA | NA | NA | 4799 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yu | NA | NA | NA | NA | 10739 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yu | NA | NA | NA | NA | 12279 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Yuan | NA | NA | NA | NA | 7081 | NA | SAVVY G | NA | FALSE | FALSE | FALSE |
| Person | Na Yuan | NA | NA | NA | NA | 14426 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zeng | NA | NA | NA | NA | 4297 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zeng | NA | NA | NA | NA | 7992 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhang | NA | NA | NA | NA | 2735 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhang | NA | NA | NA | NA | 3695 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhang | NA | NA | NA | NA | 9697 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhong | NA | NA | NA | NA | 1513 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhong | NA | NA | NA | NA | 1862 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhong | NA | NA | NA | NA | 1944 | NA | P.K. Steel | NA | FALSE | FALSE | FALSE |
| Person | Na Zhong | NA | NA | NA | NA | 10410 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhong | NA | NA | NA | NA | 13245 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhou | NA | NA | NA | NA | 6247 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhou | NA | NA | NA | NA | 7937 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhu | NA | NA | NA | NA | 4170 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhu | NA | NA | NA | NA | 14695 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zhu | NA | NA | NA | NA | 15666 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zou | NA | NA | NA | NA | 3611 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zou | NA | NA | NA | NA | 3836 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zou | NA | NA | NA | NA | 8063 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Na Zou | NA | NA | NA | NA | 14090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Nancy Arnold | NA | NA | NA | NA | 11501 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Nancy Arnold | NA | NA | NA | NA | 12885 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Nancy Smith | NA | NA | NA | NA | 3284 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Nancy Smith | NA | NA | NA | NA | 10956 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Nicole Smith | NA | NA | NA | NA | 2855 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Nicole Smith | NA | NA | NA | NA | 14261 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Bai | NA | NA | NA | NA | 356 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Bai | NA | NA | NA | NA | 968 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Bai | NA | NA | NA | NA | 1710 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Bai | NA | NA | NA | NA | 8981 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Bai | NA | NA | NA | NA | 14473 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cai | NA | NA | NA | NA | 2568 | NA | Tessa Blake | NA | FALSE | FALSE | FALSE |
| Person | Ping Cai | NA | NA | NA | NA | 9786 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cai | NA | NA | NA | NA | 14427 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cai | NA | NA | NA | NA | 16657 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cao | NA | NA | NA | NA | 4461 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cao | NA | NA | NA | NA | 4815 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Chang | NA | NA | NA | NA | 3977 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Chang | NA | NA | NA | NA | 15948 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cheng | NA | NA | NA | NA | 9750 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cheng | NA | NA | NA | NA | 10807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cui | NA | NA | NA | NA | 5108 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Cui | NA | NA | NA | NA | 8277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Deng | NA | NA | NA | NA | 6310 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Deng | NA | NA | NA | NA | 11588 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Deng | NA | NA | NA | NA | 12856 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Deng | NA | NA | NA | NA | 15003 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Ding | NA | NA | NA | NA | 841 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Ding | NA | NA | NA | NA | 2508 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Ding | NA | NA | NA | NA | 6420 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Dong | NA | NA | NA | NA | 3953 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Dong | NA | NA | NA | NA | 7112 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Dong | NA | NA | NA | NA | 11032 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Du | NA | NA | NA | NA | 4143 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Du | NA | NA | NA | NA | 10399 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Du | NA | NA | NA | NA | 10885 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Fan | NA | NA | NA | NA | 10554 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Fan | NA | NA | NA | NA | 14377 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Fu | NA | NA | NA | NA | 3693 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Fu | NA | NA | NA | NA | 4031 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Fu | NA | NA | NA | NA | 13685 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Gong | NA | NA | NA | NA | 958 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Gong | NA | NA | NA | NA | 5897 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Gong | NA | NA | NA | NA | 8432 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Gong | NA | NA | NA | NA | 16386 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Gu | NA | NA | NA | NA | 2832 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Gu | NA | NA | NA | NA | 11162 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Gu | NA | NA | NA | NA | 13845 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Guo | NA | NA | NA | NA | 2020 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Guo | NA | NA | NA | NA | 9865 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Guo | NA | NA | NA | NA | 11089 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Han | NA | NA | NA | NA | 5876 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Han | NA | NA | NA | NA | 11792 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Hao | NA | NA | NA | NA | 8659 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Hao | NA | NA | NA | NA | 9509 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Hao | NA | NA | NA | NA | 10051 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping He | NA | NA | NA | NA | 663 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping He | NA | NA | NA | NA | 1081 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping He | NA | NA | NA | NA | 6952 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping He | NA | NA | NA | NA | 7142 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping He | NA | NA | NA | NA | 7415 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping He | NA | NA | NA | NA | 14004 | NA | KING PROPH | NA | FALSE | FALSE | FALSE |
| Person | Ping He | NA | NA | NA | NA | 15113 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Hou | NA | NA | NA | NA | 3925 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Hou | NA | NA | NA | NA | 9311 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Hou | NA | NA | NA | NA | 16308 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jia | NA | NA | NA | NA | 5976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jia | NA | NA | NA | NA | 6009 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jia | NA | NA | NA | NA | 9486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jiang | NA | NA | NA | NA | 4450 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jiang | NA | NA | NA | NA | 13943 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jiang | NA | NA | NA | NA | 14917 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jin | NA | NA | NA | NA | 1317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jin | NA | NA | NA | NA | 10904 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Jin | NA | NA | NA | NA | 10927 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Lai | NA | NA | NA | NA | 4546 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Lai | NA | NA | NA | NA | 9119 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Lai | NA | NA | NA | NA | 16092 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Lei | NA | NA | NA | NA | 5244 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Lei | NA | NA | NA | NA | 6673 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Lei | NA | NA | NA | NA | 15049 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Li | NA | NA | NA | NA | 2459 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Li | NA | NA | NA | NA | 4549 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Li | NA | NA | NA | NA | 5496 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Li | NA | NA | NA | NA | 11330 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Liao | NA | NA | NA | NA | 1118 | NA | Scarlet Thorn | NA | FALSE | FALSE | FALSE |
| Person | Ping Liao | NA | NA | NA | NA | 3089 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Liao | NA | NA | NA | NA | 9157 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Liao | NA | NA | NA | NA | 10017 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Liao | NA | NA | NA | NA | 10037 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Liao | NA | NA | NA | NA | 12888 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Lu | NA | NA | NA | NA | 7522 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Lu | NA | NA | NA | NA | 12063 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Luo | NA | NA | NA | NA | 2875 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Luo | NA | NA | NA | NA | 3098 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Luo | NA | NA | NA | NA | 4780 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Luo | NA | NA | NA | NA | 8392 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Luo | NA | NA | NA | NA | 11422 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Ma | NA | NA | NA | NA | 1351 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Ma | NA | NA | NA | NA | 9783 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Mao | NA | NA | NA | NA | 6062 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Mao | NA | NA | NA | NA | 10386 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Meng | NA | NA | NA | NA | 115 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Meng | NA | NA | NA | NA | 266 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Meng | NA | NA | NA | NA | 855 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Meng | NA | NA | NA | NA | 3810 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Meng | NA | NA | NA | NA | 9733 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Meng | NA | NA | NA | NA | 12286 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Meng | NA | NA | NA | NA | 12939 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Meng | NA | NA | NA | NA | 15194 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Mo | NA | NA | NA | NA | 226 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Mo | NA | NA | NA | NA | 858 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Mo | NA | NA | NA | NA | 5622 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Mo | NA | NA | NA | NA | 7766 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Mo | NA | NA | NA | NA | 7914 | NA | Shane Walker | NA | FALSE | FALSE | FALSE |
| Person | Ping Mo | NA | NA | NA | NA | 16687 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Pan | NA | NA | NA | NA | 5054 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Pan | NA | NA | NA | NA | 14192 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Pan | NA | NA | NA | NA | 14724 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Qiao | NA | NA | NA | NA | 5221 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Qiao | NA | NA | NA | NA | 12157 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Qin | NA | NA | NA | NA | 2177 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Qin | NA | NA | NA | NA | 9508 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Qin | NA | NA | NA | NA | 15410 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Ren | NA | NA | NA | NA | 816 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Ren | NA | NA | NA | NA | 14918 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Shao | NA | NA | NA | NA | 2979 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Shao | NA | NA | NA | NA | 7879 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Shen | NA | NA | NA | NA | 5700 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Shen | NA | NA | NA | NA | 6905 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Shi | NA | NA | NA | NA | 8935 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Shi | NA | NA | NA | NA | 13248 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Song | NA | NA | NA | NA | 2297 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Song | NA | NA | NA | NA | 4113 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Song | NA | NA | NA | NA | 4448 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Song | NA | NA | NA | NA | 4491 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Song | NA | NA | NA | NA | 13433 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Su | NA | NA | NA | NA | 9334 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Su | NA | NA | NA | NA | 12159 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Sun | NA | NA | NA | NA | 1437 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Sun | NA | NA | NA | NA | 1850 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Sun | NA | NA | NA | NA | 6671 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Sun | NA | NA | NA | NA | 6834 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Sun | NA | NA | NA | NA | 14294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tan | NA | NA | NA | NA | 1005 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tan | NA | NA | NA | NA | 14468 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tang | NA | NA | NA | NA | 3159 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tang | NA | NA | NA | NA | 5820 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tao | NA | NA | NA | NA | 1468 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tao | NA | NA | NA | NA | 6172 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tao | NA | NA | NA | NA | 6355 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tian | NA | NA | NA | NA | 1648 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tian | NA | NA | NA | NA | 2668 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Tian | NA | NA | NA | NA | 15337 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wan | NA | NA | NA | NA | 9614 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wan | NA | NA | NA | NA | 9866 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wan | NA | NA | NA | NA | 15173 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wan | NA | NA | NA | NA | 15341 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wen | NA | NA | NA | NA | 10414 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wen | NA | NA | NA | NA | 13952 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wu | NA | NA | NA | NA | 3935 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wu | NA | NA | NA | NA | 4354 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wu | NA | NA | NA | NA | 11000 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wu | NA | NA | NA | NA | 14600 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Wu | NA | NA | NA | NA | 15520 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xia | NA | NA | NA | NA | 1083 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xia | NA | NA | NA | NA | 1798 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xia | NA | NA | NA | NA | 5807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xia | NA | NA | NA | NA | 12195 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xiang | NA | NA | NA | NA | 1690 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xiang | NA | NA | NA | NA | 5352 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xiang | NA | NA | NA | NA | 5360 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xiang | NA | NA | NA | NA | 14089 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xie | NA | NA | NA | NA | 664 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xie | NA | NA | NA | NA | 8089 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xie | NA | NA | NA | NA | 11610 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xu | NA | NA | NA | NA | 7078 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xu | NA | NA | NA | NA | 7277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xu | NA | NA | NA | NA | 9426 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xu | NA | NA | NA | NA | 15087 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xue | NA | NA | NA | NA | 8318 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Xue | NA | NA | NA | NA | 8965 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yan | NA | NA | NA | NA | 6999 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yan | NA | NA | NA | NA | 9015 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yan | NA | NA | NA | NA | 16114 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yao | NA | NA | NA | NA | 6228 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yao | NA | NA | NA | NA | 12733 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yao | NA | NA | NA | NA | 14194 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yu | NA | NA | NA | NA | 2084 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yu | NA | NA | NA | NA | 12442 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yu | NA | NA | NA | NA | 13613 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yuan | NA | NA | NA | NA | 4343 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Yuan | NA | NA | NA | NA | 5714 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zeng | NA | NA | NA | NA | 1785 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zeng | NA | NA | NA | NA | 15477 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhang | NA | NA | NA | NA | 637 | NA | Zara Moon | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhang | NA | NA | NA | NA | 6801 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhang | NA | NA | NA | NA | 10097 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhang | NA | NA | NA | NA | 10471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhong | NA | NA | NA | NA | 2592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhong | NA | NA | NA | NA | 4141 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhong | NA | NA | NA | NA | 15749 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhou | NA | NA | NA | NA | 1968 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhou | NA | NA | NA | NA | 4245 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhou | NA | NA | NA | NA | 11531 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ping Zhou | NA | NA | NA | NA | 16477 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Plenary Sound | NA | NA | NA | NA | 1570 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Plenary Sound | NA | NA | NA | NA | 17389 | NA | NA | NA | FALSE | FALSE | FALSE |
| Song | Postcards from Nowhere | TRUE | 2023 | Indie Folk | TRUE | 12852 | 2023 | NA | NA | FALSE | FALSE | FALSE |
| Song | Postcards from Nowhere | FALSE | 1984 | Acoustic Folk | FALSE | 17214 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Bai | NA | NA | NA | NA | 1084 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Bai | NA | NA | NA | NA | 1762 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Bai | NA | NA | NA | NA | 6586 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Bai | NA | NA | NA | NA | 6913 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cao | NA | NA | NA | NA | 13204 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cao | NA | NA | NA | NA | 15726 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Chang | NA | NA | NA | NA | 1593 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Chang | NA | NA | NA | NA | 1800 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Chang | NA | NA | NA | NA | 8022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Chang | NA | NA | NA | NA | 9317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Chang | NA | NA | NA | NA | 15845 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cheng | NA | NA | NA | NA | 1230 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cheng | NA | NA | NA | NA | 3584 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cheng | NA | NA | NA | NA | 7993 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cui | NA | NA | NA | NA | 2355 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cui | NA | NA | NA | NA | 11288 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cui | NA | NA | NA | NA | 11656 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Cui | NA | NA | NA | NA | 15952 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dai | NA | NA | NA | NA | 6846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dai | NA | NA | NA | NA | 7940 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dai | NA | NA | NA | NA | 10522 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dai | NA | NA | NA | NA | 10708 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dai | NA | NA | NA | NA | 10999 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dai | NA | NA | NA | NA | 14723 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Deng | NA | NA | NA | NA | 2895 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Deng | NA | NA | NA | NA | 3065 | NA | Lucian | NA | FALSE | FALSE | FALSE |
| Person | Qiang Ding | NA | NA | NA | NA | 9418 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Ding | NA | NA | NA | NA | 16628 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dong | NA | NA | NA | NA | 2509 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dong | NA | NA | NA | NA | 10590 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Dong | NA | NA | NA | NA | 11758 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Du | NA | NA | NA | NA | 4217 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Du | NA | NA | NA | NA | 7238 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Du | NA | NA | NA | NA | 8021 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Du | NA | NA | NA | NA | 15486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Duan | NA | NA | NA | NA | 2891 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Duan | NA | NA | NA | NA | 14952 | NA | Bronze Tiger | NA | FALSE | FALSE | FALSE |
| Person | Qiang Fan | NA | NA | NA | NA | 1622 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Fan | NA | NA | NA | NA | 7968 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Fan | NA | NA | NA | NA | 15463 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Fang | NA | NA | NA | NA | 959 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Fang | NA | NA | NA | NA | 3408 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Fang | NA | NA | NA | NA | 8299 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Fang | NA | NA | NA | NA | 15551 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Feng | NA | NA | NA | NA | 3468 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Feng | NA | NA | NA | NA | 3814 | NA | The Ghost | NA | FALSE | FALSE | FALSE |
| Person | Qiang Feng | NA | NA | NA | NA | 3840 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gao | NA | NA | NA | NA | 3315 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gao | NA | NA | NA | NA | 6568 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gao | NA | NA | NA | NA | 9863 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gao | NA | NA | NA | NA | 12236 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gao | NA | NA | NA | NA | 15018 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gu | NA | NA | NA | NA | 5602 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gu | NA | NA | NA | NA | 7109 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gu | NA | NA | NA | NA | 10096 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Gu | NA | NA | NA | NA | 10274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Han | NA | NA | NA | NA | 2336 | NA | Infinite Reverberation | NA | FALSE | FALSE | FALSE |
| Person | Qiang Han | NA | NA | NA | NA | 6373 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Han | NA | NA | NA | NA | 8294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Han | NA | NA | NA | NA | 9822 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Han | NA | NA | NA | NA | 14892 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Hao | NA | NA | NA | NA | 12659 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Hao | NA | NA | NA | NA | 15193 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang He | NA | NA | NA | NA | 1198 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang He | NA | NA | NA | NA | 3732 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Huang | NA | NA | NA | NA | 215 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Huang | NA | NA | NA | NA | 9220 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Huang | NA | NA | NA | NA | 10621 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Jiang | NA | NA | NA | NA | 5417 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Jiang | NA | NA | NA | NA | 12626 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Kang | NA | NA | NA | NA | 8007 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Kang | NA | NA | NA | NA | 13067 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lai | NA | NA | NA | NA | 475 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lai | NA | NA | NA | NA | 800 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lai | NA | NA | NA | NA | 3733 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lai | NA | NA | NA | NA | 10723 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lai | NA | NA | NA | NA | 11328 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Li | NA | NA | NA | NA | 7911 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Li | NA | NA | NA | NA | 12563 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Liu | NA | NA | NA | NA | 3988 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Liu | NA | NA | NA | NA | 4138 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Long | NA | NA | NA | NA | 13060 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Long | NA | NA | NA | NA | 13103 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lu | NA | NA | NA | NA | 1547 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lu | NA | NA | NA | NA | 11164 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lu | NA | NA | NA | NA | 11529 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lu | NA | NA | NA | NA | 13152 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Lu | NA | NA | NA | NA | 14132 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Luo | NA | NA | NA | NA | 2311 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Luo | NA | NA | NA | NA | 2543 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Luo | NA | NA | NA | NA | 7150 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Luo | NA | NA | NA | NA | 8923 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Mao | NA | NA | NA | NA | 2449 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Mao | NA | NA | NA | NA | 7789 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Mao | NA | NA | NA | NA | 9393 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Meng | NA | NA | NA | NA | 397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Meng | NA | NA | NA | NA | 9429 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Mo | NA | NA | NA | NA | 3477 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Mo | NA | NA | NA | NA | 7577 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Mo | NA | NA | NA | NA | 9742 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Mo | NA | NA | NA | NA | 11418 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Pan | NA | NA | NA | NA | 6852 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Pan | NA | NA | NA | NA | 9785 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Pan | NA | NA | NA | NA | 10171 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Pan | NA | NA | NA | NA | 13189 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Pan | NA | NA | NA | NA | 15002 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Peng | NA | NA | NA | NA | 1509 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Peng | NA | NA | NA | NA | 3437 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Peng | NA | NA | NA | NA | 3818 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Peng | NA | NA | NA | NA | 7919 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qian | NA | NA | NA | NA | 928 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qian | NA | NA | NA | NA | 5036 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qian | NA | NA | NA | NA | 6275 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qian | NA | NA | NA | NA | 12423 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qiao | NA | NA | NA | NA | 6966 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qiao | NA | NA | NA | NA | 7259 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qiao | NA | NA | NA | NA | 8887 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qin | NA | NA | NA | NA | 2060 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Qin | NA | NA | NA | NA | 6243 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Ren | NA | NA | NA | NA | 16053 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Ren | NA | NA | NA | NA | 16448 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shao | NA | NA | NA | NA | 3428 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shao | NA | NA | NA | NA | 7059 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shen | NA | NA | NA | NA | 4047 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shen | NA | NA | NA | NA | 10053 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shi | NA | NA | NA | NA | 644 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shi | NA | NA | NA | NA | 2137 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shi | NA | NA | NA | NA | 3517 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shi | NA | NA | NA | NA | 13130 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shi | NA | NA | NA | NA | 13609 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Shi | NA | NA | NA | NA | 14808 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Song | NA | NA | NA | NA | 1494 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Song | NA | NA | NA | NA | 2372 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Song | NA | NA | NA | NA | 3960 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Song | NA | NA | NA | NA | 4465 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Song | NA | NA | NA | NA | 13473 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Sun | NA | NA | NA | NA | 3889 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Sun | NA | NA | NA | NA | 10755 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Sun | NA | NA | NA | NA | 15023 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Tan | NA | NA | NA | NA | 2725 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Tan | NA | NA | NA | NA | 9521 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Tan | NA | NA | NA | NA | 12679 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Tang | NA | NA | NA | NA | 2023 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Tang | NA | NA | NA | NA | 8023 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Tao | NA | NA | NA | NA | 2929 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Tao | NA | NA | NA | NA | 6533 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Wang | NA | NA | NA | NA | 12278 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Wang | NA | NA | NA | NA | 15965 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Wei | NA | NA | NA | NA | 2938 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Wei | NA | NA | NA | NA | 12029 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Wu | NA | NA | NA | NA | 495 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Wu | NA | NA | NA | NA | 6602 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Wu | NA | NA | NA | NA | 8686 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xia | NA | NA | NA | NA | 3954 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xia | NA | NA | NA | NA | 16531 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xiang | NA | NA | NA | NA | 4696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xiang | NA | NA | NA | NA | 5626 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xiao | NA | NA | NA | NA | 9044 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xiao | NA | NA | NA | NA | 11058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xiao | NA | NA | NA | NA | 12968 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xie | NA | NA | NA | NA | 3716 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xie | NA | NA | NA | NA | 12930 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xu | NA | NA | NA | NA | 3704 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Xu | NA | NA | NA | NA | 7650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yan | NA | NA | NA | NA | 2602 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yan | NA | NA | NA | NA | 13936 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yang | NA | NA | NA | NA | 7126 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yang | NA | NA | NA | NA | 8376 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yang | NA | NA | NA | NA | 12492 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yang | NA | NA | NA | NA | 14028 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yang | NA | NA | NA | NA | 14488 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yang | NA | NA | NA | NA | 15233 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Ye | NA | NA | NA | NA | 3204 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Ye | NA | NA | NA | NA | 6963 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Ye | NA | NA | NA | NA | 16629 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yu | NA | NA | NA | NA | 2960 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yu | NA | NA | NA | NA | 4699 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yu | NA | NA | NA | NA | 12254 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yuan | NA | NA | NA | NA | 1079 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yuan | NA | NA | NA | NA | 3763 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yuan | NA | NA | NA | NA | 4298 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Yuan | NA | NA | NA | NA | 13485 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zeng | NA | NA | NA | NA | 1272 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zeng | NA | NA | NA | NA | 15544 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhang | NA | NA | NA | NA | 1403 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhang | NA | NA | NA | NA | 2365 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhang | NA | NA | NA | NA | 9156 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhang | NA | NA | NA | NA | 11639 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhao | NA | NA | NA | NA | 1200 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhao | NA | NA | NA | NA | 12815 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zheng | NA | NA | NA | NA | 354 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zheng | NA | NA | NA | NA | 3735 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhong | NA | NA | NA | NA | 5702 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhong | NA | NA | NA | NA | 12862 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhou | NA | NA | NA | NA | 877 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhou | NA | NA | NA | NA | 4761 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Qiang Zhou | NA | NA | NA | NA | 8669 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Radiant Echo | NA | NA | NA | NA | 143 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Radiant Echo | NA | NA | NA | NA | 17372 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Richard Davis | NA | NA | NA | NA | 8797 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Richard Davis | NA | NA | NA | NA | 14313 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Richard Johnson | NA | NA | NA | NA | 6134 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Richard Johnson | NA | NA | NA | NA | 13075 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Richard Rodriguez | NA | NA | NA | NA | 9405 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Richard Rodriguez | NA | NA | NA | NA | 16359 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Robert Stephens | NA | NA | NA | NA | 6394 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Robert Stephens | NA | NA | NA | NA | 12224 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Robert Stephens | NA | NA | NA | NA | 15490 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ryan Rodriguez | NA | NA | NA | NA | 9781 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ryan Rodriguez | NA | NA | NA | NA | 13352 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ryan Rodriguez | NA | NA | NA | NA | 16516 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ryohei Ito | NA | NA | NA | NA | 3656 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Ryohei Ito | NA | NA | NA | NA | 13924 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sandra Smith | NA | NA | NA | NA | 3026 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sandra Smith | NA | NA | NA | NA | 7008 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sandra Smith | NA | NA | NA | NA | 14743 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sarah Johnson | NA | NA | NA | NA | 3650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sarah Johnson | NA | NA | NA | NA | 11392 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sarah Wheeler | NA | NA | NA | NA | 11864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sarah Wheeler | NA | NA | NA | NA | 13354 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Scott Johnson | NA | NA | NA | NA | 5667 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Scott Johnson | NA | NA | NA | NA | 15320 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Serra Soundtrack | NA | NA | NA | NA | 1235 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Serra Soundtrack | NA | NA | NA | NA | 17385 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Seth Smith | NA | NA | NA | NA | 913 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Seth Smith | NA | NA | NA | NA | 11436 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sharon Sanchez | NA | NA | NA | NA | 9955 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Sharon Sanchez | NA | NA | NA | NA | 12187 | NA | NA | NA | FALSE | FALSE | FALSE |
| Album | Shattered Reflections | NA | 2013 | Emo/Pop Punk | TRUE | 3325 | 2013 | NA | 2013 | FALSE | FALSE | FALSE |
| Song | Shattered Reflections | FALSE | 2036 | Darkwave | TRUE | 17088 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Silverlight Sound | NA | NA | NA | NA | 1771 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Silverlight Sound | NA | NA | NA | NA | 17391 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Soliloquy Sounds | NA | NA | NA | NA | 1116 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Soliloquy Sounds | NA | NA | NA | NA | 17382 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Stacey Christensen | NA | NA | NA | NA | 6281 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Stacey Christensen | NA | NA | NA | NA | 9419 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | StarRoc Music | NA | NA | NA | NA | 1204 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | StarRoc Music | NA | NA | NA | NA | 17384 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Steven Boyd | NA | NA | NA | NA | 11958 | NA | Sammy Cruz | NA | FALSE | FALSE | FALSE |
| Person | Steven Boyd | NA | NA | NA | NA | 16072 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Steven Smith | NA | NA | NA | NA | 12481 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Steven Smith | NA | NA | NA | NA | 12500 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Steven Smith | NA | NA | NA | NA | 13218 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Taichi Watanabe | NA | NA | NA | NA | 7762 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Taichi Watanabe | NA | NA | NA | NA | 10766 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Bai | NA | NA | NA | NA | 3478 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Bai | NA | NA | NA | NA | 7493 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Bai | NA | NA | NA | NA | 7644 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Bai | NA | NA | NA | NA | 8683 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Bai | NA | NA | NA | NA | 8967 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Cai | NA | NA | NA | NA | 3899 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Cai | NA | NA | NA | NA | 10170 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Cai | NA | NA | NA | NA | 13288 | NA | Rain Bishop | NA | FALSE | FALSE | FALSE |
| Person | Tao Chang | NA | NA | NA | NA | 8276 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Chang | NA | NA | NA | NA | 11762 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Chang | NA | NA | NA | NA | 14726 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Chen | NA | NA | NA | NA | 2762 | NA | Dusk Fugue | NA | FALSE | FALSE | FALSE |
| Person | Tao Chen | NA | NA | NA | NA | 3090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Cui | NA | NA | NA | NA | 372 | NA | FL∆ME | NA | FALSE | FALSE | FALSE |
| Person | Tao Cui | NA | NA | NA | NA | 982 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Cui | NA | NA | NA | NA | 1752 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Cui | NA | NA | NA | NA | 7585 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Dai | NA | NA | NA | NA | 889 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Dai | NA | NA | NA | NA | 1510 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Dai | NA | NA | NA | NA | 13880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Dai | NA | NA | NA | NA | 14441 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Dai | NA | NA | NA | NA | 15554 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Deng | NA | NA | NA | NA | 6600 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Deng | NA | NA | NA | NA | 10640 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ding | NA | NA | NA | NA | 2354 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ding | NA | NA | NA | NA | 3047 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Dong | NA | NA | NA | NA | 468 | NA | Thunder Child | NA | FALSE | FALSE | FALSE |
| Person | Tao Dong | NA | NA | NA | NA | 4469 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Du | NA | NA | NA | NA | 3893 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Du | NA | NA | NA | NA | 15882 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Duan | NA | NA | NA | NA | 4458 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Duan | NA | NA | NA | NA | 6217 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Fang | NA | NA | NA | NA | 9120 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Fang | NA | NA | NA | NA | 10423 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Fang | NA | NA | NA | NA | 13285 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Fang | NA | NA | NA | NA | 14029 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Feng | NA | NA | NA | NA | 3637 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Feng | NA | NA | NA | NA | 7909 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Feng | NA | NA | NA | NA | 13807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Feng | NA | NA | NA | NA | 16144 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gao | NA | NA | NA | NA | 1240 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gao | NA | NA | NA | NA | 5011 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gao | NA | NA | NA | NA | 8880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gao | NA | NA | NA | NA | 10717 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gao | NA | NA | NA | NA | 11844 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gao | NA | NA | NA | NA | 15139 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gao | NA | NA | NA | NA | 16040 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gu | NA | NA | NA | NA | 3839 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Gu | NA | NA | NA | NA | 15428 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Guo | NA | NA | NA | NA | 6348 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Guo | NA | NA | NA | NA | 14857 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao He | NA | NA | NA | NA | 508 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao He | NA | NA | NA | NA | 6792 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao He | NA | NA | NA | NA | 9379 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Hou | NA | NA | NA | NA | 7430 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Hou | NA | NA | NA | NA | 10365 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Hou | NA | NA | NA | NA | 12696 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Hou | NA | NA | NA | NA | 15123 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Hu | NA | NA | NA | NA | 5484 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Hu | NA | NA | NA | NA | 6326 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Hu | NA | NA | NA | NA | 9804 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Hu | NA | NA | NA | NA | 14108 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Huang | NA | NA | NA | NA | 1770 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Huang | NA | NA | NA | NA | 2835 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Huang | NA | NA | NA | NA | 5251 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Huang | NA | NA | NA | NA | 14150 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Jia | NA | NA | NA | NA | 7974 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Jia | NA | NA | NA | NA | 9684 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Jia | NA | NA | NA | NA | 13371 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Jiang | NA | NA | NA | NA | 9141 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Jiang | NA | NA | NA | NA | 9592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Jiang | NA | NA | NA | NA | 13806 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Jin | NA | NA | NA | NA | 5459 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Jin | NA | NA | NA | NA | 14757 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Kang | NA | NA | NA | NA | 5006 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Kang | NA | NA | NA | NA | 11337 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Kang | NA | NA | NA | NA | 15945 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Kong | NA | NA | NA | NA | 1667 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Kong | NA | NA | NA | NA | 7634 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Kong | NA | NA | NA | NA | 12600 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Lai | NA | NA | NA | NA | 2598 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Lai | NA | NA | NA | NA | 12561 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Lei | NA | NA | NA | NA | 3068 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Lei | NA | NA | NA | NA | 3835 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Lei | NA | NA | NA | NA | 8699 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Li | NA | NA | NA | NA | 3936 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Li | NA | NA | NA | NA | 10273 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Liao | NA | NA | NA | NA | 206 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Liao | NA | NA | NA | NA | 2995 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Liao | NA | NA | NA | NA | 8391 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Liao | NA | NA | NA | NA | 13400 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Liao | NA | NA | NA | NA | 15860 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Lin | NA | NA | NA | NA | 6220 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Lin | NA | NA | NA | NA | 6817 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Liu | NA | NA | NA | NA | 774 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Liu | NA | NA | NA | NA | 5717 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Liu | NA | NA | NA | NA | 6460 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Long | NA | NA | NA | NA | 1315 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Long | NA | NA | NA | NA | 5253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Luo | NA | NA | NA | NA | 3796 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Luo | NA | NA | NA | NA | 12966 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ma | NA | NA | NA | NA | 5250 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ma | NA | NA | NA | NA | 14806 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Mao | NA | NA | NA | NA | 11497 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Mao | NA | NA | NA | NA | 13099 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Meng | NA | NA | NA | NA | 4291 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Meng | NA | NA | NA | NA | 6094 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Mo | NA | NA | NA | NA | 1004 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Mo | NA | NA | NA | NA | 1072 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Mo | NA | NA | NA | NA | 15575 | NA | Halogen Visions | NA | FALSE | FALSE | FALSE |
| Person | Tao Mo | NA | NA | NA | NA | 15614 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Pan | NA | NA | NA | NA | 6077 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Pan | NA | NA | NA | NA | 7340 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Pan | NA | NA | NA | NA | 10029 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Peng | NA | NA | NA | NA | 1283 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Peng | NA | NA | NA | NA | 5234 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Peng | NA | NA | NA | NA | 6149 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Peng | NA | NA | NA | NA | 12854 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Qian | NA | NA | NA | NA | 9325 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Qian | NA | NA | NA | NA | 10003 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Qiao | NA | NA | NA | NA | 1231 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Qiao | NA | NA | NA | NA | 4934 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Qiao | NA | NA | NA | NA | 16218 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Qin | NA | NA | NA | NA | 374 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Qin | NA | NA | NA | NA | 7986 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ren | NA | NA | NA | NA | 2910 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ren | NA | NA | NA | NA | 3490 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ren | NA | NA | NA | NA | 8643 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ren | NA | NA | NA | NA | 10897 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ren | NA | NA | NA | NA | 16594 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Shao | NA | NA | NA | NA | 10172 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Shao | NA | NA | NA | NA | 10784 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Shen | NA | NA | NA | NA | 1398 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Shen | NA | NA | NA | NA | 8088 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Shen | NA | NA | NA | NA | 9814 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Shen | NA | NA | NA | NA | 12310 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Song | NA | NA | NA | NA | 8360 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Song | NA | NA | NA | NA | 8377 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Song | NA | NA | NA | NA | 12813 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Su | NA | NA | NA | NA | 2315 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Su | NA | NA | NA | NA | 6414 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Su | NA | NA | NA | NA | 6646 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Su | NA | NA | NA | NA | 11582 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Su | NA | NA | NA | NA | 11782 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Sun | NA | NA | NA | NA | 2590 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Sun | NA | NA | NA | NA | 2669 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Sun | NA | NA | NA | NA | 2836 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Sun | NA | NA | NA | NA | 6835 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Sun | NA | NA | NA | NA | 11133 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Tang | NA | NA | NA | NA | 3720 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Tang | NA | NA | NA | NA | 7642 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Tang | NA | NA | NA | NA | 9731 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Tang | NA | NA | NA | NA | 11320 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Tao | NA | NA | NA | NA | 4116 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Tao | NA | NA | NA | NA | 7905 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Wei | NA | NA | NA | NA | 199 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Wei | NA | NA | NA | NA | 8162 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Wei | NA | NA | NA | NA | 8724 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Wei | NA | NA | NA | NA | 9894 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Wen | NA | NA | NA | NA | 4096 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Wen | NA | NA | NA | NA | 10905 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xiang | NA | NA | NA | NA | 10079 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xiang | NA | NA | NA | NA | 15213 | NA | Velvet Rook | NA | FALSE | FALSE | FALSE |
| Person | Tao Xie | NA | NA | NA | NA | 3413 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xie | NA | NA | NA | NA | 7849 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xie | NA | NA | NA | NA | 15223 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xiong | NA | NA | NA | NA | 2477 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xiong | NA | NA | NA | NA | 12778 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xiong | NA | NA | NA | NA | 15955 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xu | NA | NA | NA | NA | 4592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xu | NA | NA | NA | NA | 10162 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xu | NA | NA | NA | NA | 10271 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xu | NA | NA | NA | NA | 11781 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Xu | NA | NA | NA | NA | 12152 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yan | NA | NA | NA | NA | 367 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yan | NA | NA | NA | NA | 10387 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yan | NA | NA | NA | NA | 12579 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yang | NA | NA | NA | NA | 566 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yang | NA | NA | NA | NA | 617 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yang | NA | NA | NA | NA | 4860 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yao | NA | NA | NA | NA | 203 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yao | NA | NA | NA | NA | 5107 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yao | NA | NA | NA | NA | 6534 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yao | NA | NA | NA | NA | 16089 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ye | NA | NA | NA | NA | 4347 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Ye | NA | NA | NA | NA | 9097 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yin | NA | NA | NA | NA | 3887 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yin | NA | NA | NA | NA | 4176 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yin | NA | NA | NA | NA | 4396 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yin | NA | NA | NA | NA | 7134 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yin | NA | NA | NA | NA | 10670 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yu | NA | NA | NA | NA | 4203 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yu | NA | NA | NA | NA | 10078 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yu | NA | NA | NA | NA | 12879 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yu | NA | NA | NA | NA | 15468 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yuan | NA | NA | NA | NA | 3278 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yuan | NA | NA | NA | NA | 11892 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Yuan | NA | NA | NA | NA | 13988 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zeng | NA | NA | NA | NA | 50 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zeng | NA | NA | NA | NA | 4553 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zeng | NA | NA | NA | NA | 4632 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhang | NA | NA | NA | NA | 4125 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhang | NA | NA | NA | NA | 7144 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhang | NA | NA | NA | NA | 10786 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhang | NA | NA | NA | NA | 15147 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhang | NA | NA | NA | NA | 16267 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhao | NA | NA | NA | NA | 1865 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhao | NA | NA | NA | NA | 8677 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhao | NA | NA | NA | NA | 10895 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zheng | NA | NA | NA | NA | 3808 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zheng | NA | NA | NA | NA | 7164 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zheng | NA | NA | NA | NA | 13700 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhou | NA | NA | NA | NA | 2371 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhou | NA | NA | NA | NA | 11145 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhu | NA | NA | NA | NA | 8807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhu | NA | NA | NA | NA | 10607 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zhu | NA | NA | NA | NA | 12470 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zou | NA | NA | NA | NA | 273 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zou | NA | NA | NA | NA | 1619 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Tao Zou | NA | NA | NA | NA | 5733 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Thomas Brown | NA | NA | NA | NA | 10630 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Thomas Brown | NA | NA | NA | NA | 13661 | NA | DA VINCI | NA | FALSE | FALSE | FALSE |
| Person | Timothy Moore | NA | NA | NA | NA | 14479 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Timothy Moore | NA | NA | NA | NA | 15824 | NA | NA | NA | FALSE | FALSE | FALSE |
| Song | Unheard Frequencies | TRUE | 2025 | Alternative Rock | TRUE | 7999 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Unheard Frequencies | NA | NA | NA | NA | 10952 | NA | NA | NA | FALSE | FALSE | FALSE |
| Song | Vanishing Point | TRUE | 2018 | Avant-Garde Folk | TRUE | 9371 | 2018 | NA | NA | FALSE | FALSE | FALSE |
| Song | Vanishing Point | FALSE | 2013 | Oceanus Folk | FALSE | 17338 | NA | NA | NA | FALSE | FALSE | TRUE |
| RecordLabel | Vertical Altitude | NA | NA | NA | NA | 1925 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Vertical Altitude | NA | NA | NA | NA | 17393 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Vertical Ascent Records | NA | NA | NA | NA | 797 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Vertical Ascent Records | NA | NA | NA | NA | 17377 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Vertical Horizon | NA | NA | NA | NA | 2453 | NA | NA | NA | FALSE | FALSE | FALSE |
| Album | Vertical Horizon | NA | 2017 | Doom Metal | TRUE | 9262 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Vicki Morgan | NA | NA | NA | NA | 6682 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Vicki Morgan | NA | NA | NA | NA | 9247 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Bai | NA | NA | NA | NA | 399 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Bai | NA | NA | NA | NA | 7239 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cai | NA | NA | NA | NA | 7193 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cai | NA | NA | NA | NA | 12621 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cai | NA | NA | NA | NA | 15152 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cao | NA | NA | NA | NA | 859 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cao | NA | NA | NA | NA | 1267 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cao | NA | NA | NA | NA | 1354 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cao | NA | NA | NA | NA | 4309 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Chang | NA | NA | NA | NA | 3833 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Chang | NA | NA | NA | NA | 8298 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cheng | NA | NA | NA | NA | 8156 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cheng | NA | NA | NA | NA | 15569 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cui | NA | NA | NA | NA | 2981 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Cui | NA | NA | NA | NA | 11260 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Dai | NA | NA | NA | NA | 5895 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Dai | NA | NA | NA | NA | 6962 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Dai | NA | NA | NA | NA | 15074 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Ding | NA | NA | NA | NA | 1099 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Ding | NA | NA | NA | NA | 12741 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Du | NA | NA | NA | NA | 8212 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Du | NA | NA | NA | NA | 12711 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Fan | NA | NA | NA | NA | 8186 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Fan | NA | NA | NA | NA | 10891 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gao | NA | NA | NA | NA | 578 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gao | NA | NA | NA | NA | 1647 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gao | NA | NA | NA | NA | 1878 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gao | NA | NA | NA | NA | 11648 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gu | NA | NA | NA | NA | 5940 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gu | NA | NA | NA | NA | 7352 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gu | NA | NA | NA | NA | 7443 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gu | NA | NA | NA | NA | 13624 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gu | NA | NA | NA | NA | 15719 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Gu | NA | NA | NA | NA | 16257 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Guo | NA | NA | NA | NA | 2155 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Guo | NA | NA | NA | NA | 10923 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei He | NA | NA | NA | NA | 2022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei He | NA | NA | NA | NA | 4041 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei He | NA | NA | NA | NA | 6744 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei He | NA | NA | NA | NA | 9879 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Hu | NA | NA | NA | NA | 3032 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Hu | NA | NA | NA | NA | 12312 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Huang | NA | NA | NA | NA | 3096 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Huang | NA | NA | NA | NA | 7848 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Huang | NA | NA | NA | NA | 9734 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Jia | NA | NA | NA | NA | 7792 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Jia | NA | NA | NA | NA | 13172 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Jia | NA | NA | NA | NA | 15796 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Kang | NA | NA | NA | NA | 2252 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Kang | NA | NA | NA | NA | 6079 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Kang | NA | NA | NA | NA | 15079 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Kong | NA | NA | NA | NA | 13467 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Kong | NA | NA | NA | NA | 13896 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lei | NA | NA | NA | NA | 4295 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lei | NA | NA | NA | NA | 14869 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Li | NA | NA | NA | NA | 499 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Li | NA | NA | NA | NA | 11593 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Li | NA | NA | NA | NA | 14390 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liang | NA | NA | NA | NA | 3201 | NA | Valoria | NA | FALSE | FALSE | FALSE |
| Person | Wei Liang | NA | NA | NA | NA | 7135 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liang | NA | NA | NA | NA | 10908 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liang | NA | NA | NA | NA | 11920 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liao | NA | NA | NA | NA | 887 | NA | B.D. Wolf | NA | FALSE | FALSE | FALSE |
| Person | Wei Liao | NA | NA | NA | NA | 2089 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liao | NA | NA | NA | NA | 3276 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liao | NA | NA | NA | NA | 9765 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liao | NA | NA | NA | NA | 12400 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liao | NA | NA | NA | NA | 15148 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liao | NA | NA | NA | NA | 15155 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lin | NA | NA | NA | NA | 8363 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lin | NA | NA | NA | NA | 9127 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lin | NA | NA | NA | NA | 9726 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lin | NA | NA | NA | NA | 14833 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liu | NA | NA | NA | NA | 5613 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liu | NA | NA | NA | NA | 7136 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liu | NA | NA | NA | NA | 10649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Liu | NA | NA | NA | NA | 12421 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Long | NA | NA | NA | NA | 3739 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Long | NA | NA | NA | NA | 5420 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Long | NA | NA | NA | NA | 14719 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lu | NA | NA | NA | NA | 2313 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lu | NA | NA | NA | NA | 3292 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Lu | NA | NA | NA | NA | 14092 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Luo | NA | NA | NA | NA | 4053 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Luo | NA | NA | NA | NA | 12482 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Luo | NA | NA | NA | NA | 12880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Luo | NA | NA | NA | NA | 13141 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Ma | NA | NA | NA | NA | 6998 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Ma | NA | NA | NA | NA | 9959 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mao | NA | NA | NA | NA | 359 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mao | NA | NA | NA | NA | 1682 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mao | NA | NA | NA | NA | 9440 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mao | NA | NA | NA | NA | 16680 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Meng | NA | NA | NA | NA | 501 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Meng | NA | NA | NA | NA | 5822 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Meng | NA | NA | NA | NA | 10902 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mo | NA | NA | NA | NA | 565 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mo | NA | NA | NA | NA | 2635 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mo | NA | NA | NA | NA | 2902 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mo | NA | NA | NA | NA | 4896 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mo | NA | NA | NA | NA | 8184 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Mo | NA | NA | NA | NA | 13830 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Pan | NA | NA | NA | NA | 2095 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Pan | NA | NA | NA | NA | 2829 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Pan | NA | NA | NA | NA | 10265 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Pan | NA | NA | NA | NA | 11507 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Peng | NA | NA | NA | NA | 8984 | NA | Nebula Prince | NA | FALSE | FALSE | FALSE |
| Person | Wei Peng | NA | NA | NA | NA | 14773 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Peng | NA | NA | NA | NA | 15471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Peng | NA | NA | NA | NA | 16132 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Qian | NA | NA | NA | NA | 5886 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Qian | NA | NA | NA | NA | 8847 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Qian | NA | NA | NA | NA | 11486 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Qiao | NA | NA | NA | NA | 13119 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Qiao | NA | NA | NA | NA | 15753 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Qiu | NA | NA | NA | NA | 8327 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Qiu | NA | NA | NA | NA | 12541 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Qiu | NA | NA | NA | NA | 14334 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shao | NA | NA | NA | NA | 6374 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shao | NA | NA | NA | NA | 11038 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shen | NA | NA | NA | NA | 3209 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shen | NA | NA | NA | NA | 5531 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shen | NA | NA | NA | NA | 6559 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shen | NA | NA | NA | NA | 14189 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shi | NA | NA | NA | NA | 3703 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shi | NA | NA | NA | NA | 5030 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shi | NA | NA | NA | NA | 6184 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shi | NA | NA | NA | NA | 9993 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Shi | NA | NA | NA | NA | 11039 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Su | NA | NA | NA | NA | 483 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Su | NA | NA | NA | NA | 1766 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Su | NA | NA | NA | NA | 3994 | NA | Alex Stone | NA | FALSE | FALSE | FALSE |
| Person | Wei Su | NA | NA | NA | NA | 15879 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Sun | NA | NA | NA | NA | 6345 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Sun | NA | NA | NA | NA | 14178 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tan | NA | NA | NA | NA | 3877 | NA | Waytawn | NA | FALSE | FALSE | FALSE |
| Person | Wei Tan | NA | NA | NA | NA | 6500 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tan | NA | NA | NA | NA | 13388 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tang | NA | NA | NA | NA | 142 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tang | NA | NA | NA | NA | 10027 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tao | NA | NA | NA | NA | 7202 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tao | NA | NA | NA | NA | 11496 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tian | NA | NA | NA | NA | 7343 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tian | NA | NA | NA | NA | 11373 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Tian | NA | NA | NA | NA | 15693 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wan | NA | NA | NA | NA | 2643 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wan | NA | NA | NA | NA | 5390 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wan | NA | NA | NA | NA | 7976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wan | NA | NA | NA | NA | 12663 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wan | NA | NA | NA | NA | 12738 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wan | NA | NA | NA | NA | 13289 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wang | NA | NA | NA | NA | 2907 | NA | Caleb Stone | NA | FALSE | FALSE | FALSE |
| Person | Wei Wang | NA | NA | NA | NA | 2992 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wang | NA | NA | NA | NA | 7108 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wang | NA | NA | NA | NA | 11348 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wen | NA | NA | NA | NA | 12912 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wen | NA | NA | NA | NA | 14317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wu | NA | NA | NA | NA | 198 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wu | NA | NA | NA | NA | 10888 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wu | NA | NA | NA | NA | 14791 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Wu | NA | NA | NA | NA | 16081 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xia | NA | NA | NA | NA | 8334 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xia | NA | NA | NA | NA | 10122 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiao | NA | NA | NA | NA | 360 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiao | NA | NA | NA | NA | 3489 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiao | NA | NA | NA | NA | 14807 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiao | NA | NA | NA | NA | 15476 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiong | NA | NA | NA | NA | 3642 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiong | NA | NA | NA | NA | 3765 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiong | NA | NA | NA | NA | 8451 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiong | NA | NA | NA | NA | 13407 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xiong | NA | NA | NA | NA | 16074 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xu | NA | NA | NA | NA | 3023 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xu | NA | NA | NA | NA | 13980 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xue | NA | NA | NA | NA | 1695 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Xue | NA | NA | NA | NA | 9169 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yao | NA | NA | NA | NA | 6557 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yao | NA | NA | NA | NA | 7404 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yao | NA | NA | NA | NA | 10605 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yao | NA | NA | NA | NA | 14993 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yao | NA | NA | NA | NA | 16193 | NA | XANOVA | NA | FALSE | FALSE | FALSE |
| Person | Wei Ye | NA | NA | NA | NA | 116 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Ye | NA | NA | NA | NA | 9757 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Ye | NA | NA | NA | NA | 12555 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Ye | NA | NA | NA | NA | 13193 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yin | NA | NA | NA | NA | 3639 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yin | NA | NA | NA | NA | 10832 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yu | NA | NA | NA | NA | 3322 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yu | NA | NA | NA | NA | 10015 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yuan | NA | NA | NA | NA | 4608 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yuan | NA | NA | NA | NA | 7480 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Yuan | NA | NA | NA | NA | 12473 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zeng | NA | NA | NA | NA | 5350 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zeng | NA | NA | NA | NA | 5649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zeng | NA | NA | NA | NA | 15904 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhang | NA | NA | NA | NA | 265 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhang | NA | NA | NA | NA | 6842 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhang | NA | NA | NA | NA | 14591 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhang | NA | NA | NA | NA | 16650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhao | NA | NA | NA | NA | 2860 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhao | NA | NA | NA | NA | 3764 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhao | NA | NA | NA | NA | 5645 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhao | NA | NA | NA | NA | 13590 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zheng | NA | NA | NA | NA | 5176 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zheng | NA | NA | NA | NA | 7812 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhong | NA | NA | NA | NA | 5349 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhong | NA | NA | NA | NA | 16511 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhu | NA | NA | NA | NA | 2757 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zhu | NA | NA | NA | NA | 14548 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zou | NA | NA | NA | NA | 15417 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Wei Zou | NA | NA | NA | NA | 15562 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | William Brown | NA | NA | NA | NA | 2258 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | William Brown | NA | NA | NA | NA | 9359 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | William Rodriguez | NA | NA | NA | NA | 1454 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | William Rodriguez | NA | NA | NA | NA | 4823 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Bai | NA | NA | NA | NA | 4698 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Bai | NA | NA | NA | NA | 7957 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Bai | NA | NA | NA | NA | 11891 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Cai | NA | NA | NA | NA | 1761 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Cai | NA | NA | NA | NA | 4311 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Cai | NA | NA | NA | NA | 6626 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Cai | NA | NA | NA | NA | 10299 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Chang | NA | NA | NA | NA | 135 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Chang | NA | NA | NA | NA | 5821 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Chang | NA | NA | NA | NA | 12256 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Chen | NA | NA | NA | NA | 398 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Chen | NA | NA | NA | NA | 3686 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Chen | NA | NA | NA | NA | 10433 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Cui | NA | NA | NA | NA | 4395 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Cui | NA | NA | NA | NA | 6125 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Cui | NA | NA | NA | NA | 6889 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Dai | NA | NA | NA | NA | 5368 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Dai | NA | NA | NA | NA | 8850 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Dai | NA | NA | NA | NA | 11559 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Dai | NA | NA | NA | NA | 12901 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Dai | NA | NA | NA | NA | 15460 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Deng | NA | NA | NA | NA | 3410 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Deng | NA | NA | NA | NA | 9453 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Du | NA | NA | NA | NA | 813 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Du | NA | NA | NA | NA | 1362 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Du | NA | NA | NA | NA | 4075 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Du | NA | NA | NA | NA | 4358 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Du | NA | NA | NA | NA | 11580 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Duan | NA | NA | NA | NA | 4778 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Duan | NA | NA | NA | NA | 12298 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Fan | NA | NA | NA | NA | 3320 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Fan | NA | NA | NA | NA | 13946 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Fang | NA | NA | NA | NA | 1165 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Fang | NA | NA | NA | NA | 10925 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Fang | NA | NA | NA | NA | 13409 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Fang | NA | NA | NA | NA | 13773 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Feng | NA | NA | NA | NA | 2976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Feng | NA | NA | NA | NA | 16260 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Fu | NA | NA | NA | NA | 149 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Fu | NA | NA | NA | NA | 7815 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Gu | NA | NA | NA | NA | 9464 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Gu | NA | NA | NA | NA | 11344 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Guo | NA | NA | NA | NA | 9310 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Guo | NA | NA | NA | NA | 12765 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Han | NA | NA | NA | NA | 8072 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Han | NA | NA | NA | NA | 12314 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Han | NA | NA | NA | NA | 14703 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Hao | NA | NA | NA | NA | 3927 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Hao | NA | NA | NA | NA | 11340 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Hu | NA | NA | NA | NA | 2268 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Hu | NA | NA | NA | NA | 6388 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Hu | NA | NA | NA | NA | 9668 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Hu | NA | NA | NA | NA | 13308 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Jia | NA | NA | NA | NA | 3028 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Jia | NA | NA | NA | NA | 4356 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Jia | NA | NA | NA | NA | 11165 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Jin | NA | NA | NA | NA | 2276 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Jin | NA | NA | NA | NA | 13061 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Jin | NA | NA | NA | NA | 13743 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Jin | NA | NA | NA | NA | 15924 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Kang | NA | NA | NA | NA | 7020 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Kang | NA | NA | NA | NA | 10756 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Kang | NA | NA | NA | NA | 12128 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Kang | NA | NA | NA | NA | 12701 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lei | NA | NA | NA | NA | 2136 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lei | NA | NA | NA | NA | 2727 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lei | NA | NA | NA | NA | 8589 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Li | NA | NA | NA | NA | 393 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Li | NA | NA | NA | NA | 2393 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Li | NA | NA | NA | NA | 4918 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Li | NA | NA | NA | NA | 6650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Li | NA | NA | NA | NA | 6711 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Li | NA | NA | NA | NA | 9302 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Liang | NA | NA | NA | NA | 1300 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Liang | NA | NA | NA | NA | 5676 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Liang | NA | NA | NA | NA | 11823 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Liang | NA | NA | NA | NA | 12488 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Liao | NA | NA | NA | NA | 5252 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Liao | NA | NA | NA | NA | 10808 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lin | NA | NA | NA | NA | 2314 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lin | NA | NA | NA | NA | 2601 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lin | NA | NA | NA | NA | 5222 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lin | NA | NA | NA | NA | 5545 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lin | NA | NA | NA | NA | 7262 | NA | Knight IX | NA | FALSE | FALSE | FALSE |
| Person | Xia Long | NA | NA | NA | NA | 5454 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Long | NA | NA | NA | NA | 6982 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lu | NA | NA | NA | NA | 812 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Lu | NA | NA | NA | NA | 1744 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ma | NA | NA | NA | NA | 2862 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ma | NA | NA | NA | NA | 7816 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ma | NA | NA | NA | NA | 14184 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Mao | NA | NA | NA | NA | 12430 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Mao | NA | NA | NA | NA | 13695 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Meng | NA | NA | NA | NA | 8897 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Meng | NA | NA | NA | NA | 12655 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Pan | NA | NA | NA | NA | 5262 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Pan | NA | NA | NA | NA | 7328 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Pan | NA | NA | NA | NA | 16537 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qian | NA | NA | NA | NA | 14620 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qian | NA | NA | NA | NA | 15859 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qiao | NA | NA | NA | NA | 7587 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qiao | NA | NA | NA | NA | 10646 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qiao | NA | NA | NA | NA | 12726 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qin | NA | NA | NA | NA | 5200 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qin | NA | NA | NA | NA | 7072 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qin | NA | NA | NA | NA | 7720 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qin | NA | NA | NA | NA | 12648 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qiu | NA | NA | NA | NA | 6862 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Qiu | NA | NA | NA | NA | 15483 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ren | NA | NA | NA | NA | 197 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ren | NA | NA | NA | NA | 2293 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ren | NA | NA | NA | NA | 6914 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ren | NA | NA | NA | NA | 14714 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Shao | NA | NA | NA | NA | 11132 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Shao | NA | NA | NA | NA | 13445 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Shen | NA | NA | NA | NA | 295 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Shen | NA | NA | NA | NA | 15976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Song | NA | NA | NA | NA | 3929 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Song | NA | NA | NA | NA | 10224 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Su | NA | NA | NA | NA | 7962 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Su | NA | NA | NA | NA | 15128 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tan | NA | NA | NA | NA | 2139 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tan | NA | NA | NA | NA | 4986 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tan | NA | NA | NA | NA | 5211 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tan | NA | NA | NA | NA | 9423 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tang | NA | NA | NA | NA | 6574 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tang | NA | NA | NA | NA | 9675 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tang | NA | NA | NA | NA | 11087 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tang | NA | NA | NA | NA | 11853 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tian | NA | NA | NA | NA | 3924 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tian | NA | NA | NA | NA | 13020 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Tian | NA | NA | NA | NA | 15356 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wan | NA | NA | NA | NA | 6585 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wan | NA | NA | NA | NA | 15331 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wan | NA | NA | NA | NA | 16167 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wang | NA | NA | NA | NA | 903 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wang | NA | NA | NA | NA | 10823 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wang | NA | NA | NA | NA | 13443 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wei | NA | NA | NA | NA | 5270 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wei | NA | NA | NA | NA | 14430 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wen | NA | NA | NA | NA | 8418 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wen | NA | NA | NA | NA | 13163 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wu | NA | NA | NA | NA | 141 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wu | NA | NA | NA | NA | 6206 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wu | NA | NA | NA | NA | 12527 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Wu | NA | NA | NA | NA | 15265 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xia | NA | NA | NA | NA | 2932 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xia | NA | NA | NA | NA | 7024 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xia | NA | NA | NA | NA | 15263 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xiao | NA | NA | NA | NA | 10339 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xiao | NA | NA | NA | NA | 15465 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xiong | NA | NA | NA | NA | 752 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xiong | NA | NA | NA | NA | 6013 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xiong | NA | NA | NA | NA | 6403 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xiong | NA | NA | NA | NA | 14081 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xu | NA | NA | NA | NA | 11539 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xu | NA | NA | NA | NA | 14925 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xue | NA | NA | NA | NA | 4816 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xue | NA | NA | NA | NA | 5912 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Xue | NA | NA | NA | NA | 7096 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yang | NA | NA | NA | NA | 49 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yang | NA | NA | NA | NA | 7051 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yang | NA | NA | NA | NA | 15125 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yao | NA | NA | NA | NA | 1643 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yao | NA | NA | NA | NA | 2901 | NA | Zephara | NA | FALSE | FALSE | FALSE |
| Person | Xia Ye | NA | NA | NA | NA | 668 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ye | NA | NA | NA | NA | 7132 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Ye | NA | NA | NA | NA | 15385 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yin | NA | NA | NA | NA | 2565 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yin | NA | NA | NA | NA | 15869 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yu | NA | NA | NA | NA | 5401 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yu | NA | NA | NA | NA | 11277 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yu | NA | NA | NA | NA | 12272 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yuan | NA | NA | NA | NA | 3789 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yuan | NA | NA | NA | NA | 6295 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yuan | NA | NA | NA | NA | 10020 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yuan | NA | NA | NA | NA | 10497 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Yuan | NA | NA | NA | NA | 10506 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zeng | NA | NA | NA | NA | 1266 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zeng | NA | NA | NA | NA | 2324 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zeng | NA | NA | NA | NA | 5573 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zeng | NA | NA | NA | NA | 6025 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zeng | NA | NA | NA | NA | 6622 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zeng | NA | NA | NA | NA | 6783 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zeng | NA | NA | NA | NA | 7201 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhang | NA | NA | NA | NA | 6823 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhang | NA | NA | NA | NA | 7405 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhang | NA | NA | NA | NA | 11106 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhang | NA | NA | NA | NA | 16337 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhao | NA | NA | NA | NA | 5445 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhao | NA | NA | NA | NA | 12529 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zheng | NA | NA | NA | NA | 4359 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zheng | NA | NA | NA | NA | 12857 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhou | NA | NA | NA | NA | 6891 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhou | NA | NA | NA | NA | 9166 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhou | NA | NA | NA | NA | 13317 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhu | NA | NA | NA | NA | 3460 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xia Zhu | NA | NA | NA | NA | 8726 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Cai | NA | NA | NA | NA | 5542 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Cai | NA | NA | NA | NA | 15548 | NA | Nocturne | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Cao | NA | NA | NA | NA | 4972 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Cao | NA | NA | NA | NA | 5793 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Cao | NA | NA | NA | NA | 6772 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Cao | NA | NA | NA | NA | 6853 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Chang | NA | NA | NA | NA | 1522 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Chang | NA | NA | NA | NA | 2339 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Chang | NA | NA | NA | NA | 3296 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Cheng | NA | NA | NA | NA | 4468 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Cheng | NA | NA | NA | NA | 11421 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Deng | NA | NA | NA | NA | 2211 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Deng | NA | NA | NA | NA | 3496 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Deng | NA | NA | NA | NA | 12654 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Dong | NA | NA | NA | NA | 1861 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Dong | NA | NA | NA | NA | 4324 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Dong | NA | NA | NA | NA | 8108 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Dong | NA | NA | NA | NA | 9168 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Dong | NA | NA | NA | NA | 11874 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Du | NA | NA | NA | NA | 2911 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Du | NA | NA | NA | NA | 4864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Du | NA | NA | NA | NA | 12695 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Du | NA | NA | NA | NA | 14561 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Du | NA | NA | NA | NA | 15585 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Duan | NA | NA | NA | NA | 7410 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Duan | NA | NA | NA | NA | 10272 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Duan | NA | NA | NA | NA | 14341 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Duan | NA | NA | NA | NA | 14541 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Feng | NA | NA | NA | NA | 3412 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Feng | NA | NA | NA | NA | 6545 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Feng | NA | NA | NA | NA | 8588 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Fu | NA | NA | NA | NA | 2011 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Fu | NA | NA | NA | NA | 11856 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Fu | NA | NA | NA | NA | 15514 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gong | NA | NA | NA | NA | 1073 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gong | NA | NA | NA | NA | 1594 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gong | NA | NA | NA | NA | 2163 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gong | NA | NA | NA | NA | 7437 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gong | NA | NA | NA | NA | 7767 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gong | NA | NA | NA | NA | 10036 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gu | NA | NA | NA | NA | 8792 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gu | NA | NA | NA | NA | 10050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Gu | NA | NA | NA | NA | 12364 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hao | NA | NA | NA | NA | 1255 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hao | NA | NA | NA | NA | 4976 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hao | NA | NA | NA | NA | 6291 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hao | NA | NA | NA | NA | 12839 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan He | NA | NA | NA | NA | 614 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan He | NA | NA | NA | NA | 12206 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan He | NA | NA | NA | NA | 14725 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan He | NA | NA | NA | NA | 15453 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hou | NA | NA | NA | NA | 2940 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hou | NA | NA | NA | NA | 16307 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hou | NA | NA | NA | NA | 16550 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hu | NA | NA | NA | NA | 953 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hu | NA | NA | NA | NA | 5735 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Hu | NA | NA | NA | NA | 13740 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Huang | NA | NA | NA | NA | 294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Huang | NA | NA | NA | NA | 6959 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Jia | NA | NA | NA | NA | 10886 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Jia | NA | NA | NA | NA | 13512 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Jiang | NA | NA | NA | NA | 3097 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Jiang | NA | NA | NA | NA | 12334 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Kang | NA | NA | NA | NA | 1274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Kang | NA | NA | NA | NA | 8411 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Kang | NA | NA | NA | NA | 11194 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lai | NA | NA | NA | NA | 6083 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lai | NA | NA | NA | NA | 11798 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lei | NA | NA | NA | NA | 956 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lei | NA | NA | NA | NA | 2450 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Li | NA | NA | NA | NA | 90 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Li | NA | NA | NA | NA | 4707 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Li | NA | NA | NA | NA | 16000 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liang | NA | NA | NA | NA | 3137 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liang | NA | NA | NA | NA | 3525 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liang | NA | NA | NA | NA | 9704 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liang | NA | NA | NA | NA | 13919 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liang | NA | NA | NA | NA | 15671 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liao | NA | NA | NA | NA | 1288 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liao | NA | NA | NA | NA | 2716 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liao | NA | NA | NA | NA | 7753 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liao | NA | NA | NA | NA | 8187 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lin | NA | NA | NA | NA | 890 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lin | NA | NA | NA | NA | 2584 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lin | NA | NA | NA | NA | 3762 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lin | NA | NA | NA | NA | 15550 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liu | NA | NA | NA | NA | 1385 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liu | NA | NA | NA | NA | 4982 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liu | NA | NA | NA | NA | 12153 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Liu | NA | NA | NA | NA | 16219 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lu | NA | NA | NA | NA | 2686 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lu | NA | NA | NA | NA | 3248 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lu | NA | NA | NA | NA | 3868 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lu | NA | NA | NA | NA | 4004 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lu | NA | NA | NA | NA | 6071 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lu | NA | NA | NA | NA | 11977 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Lu | NA | NA | NA | NA | 15149 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ma | NA | NA | NA | NA | 2451 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ma | NA | NA | NA | NA | 4617 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ma | NA | NA | NA | NA | 8020 | NA | Luca West | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ma | NA | NA | NA | NA | 15615 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Meng | NA | NA | NA | NA | 4988 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Meng | NA | NA | NA | NA | 5874 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Meng | NA | NA | NA | NA | 12406 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Mo | NA | NA | NA | NA | 1646 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Mo | NA | NA | NA | NA | 5768 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Mo | NA | NA | NA | NA | 10427 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Mo | NA | NA | NA | NA | 13435 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Mo | NA | NA | NA | NA | 15517 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Qin | NA | NA | NA | NA | 2135 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Qin | NA | NA | NA | NA | 4040 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Qin | NA | NA | NA | NA | 6056 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Qin | NA | NA | NA | NA | 15395 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Qin | NA | NA | NA | NA | 16058 | NA | DA PROPHET | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ren | NA | NA | NA | NA | 829 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ren | NA | NA | NA | NA | 1698 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ren | NA | NA | NA | NA | 3445 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ren | NA | NA | NA | NA | 3961 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ren | NA | NA | NA | NA | 7120 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ren | NA | NA | NA | NA | 10988 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shao | NA | NA | NA | NA | 2054 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shao | NA | NA | NA | NA | 8362 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shao | NA | NA | NA | NA | 10721 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shen | NA | NA | NA | NA | 592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shen | NA | NA | NA | NA | 10009 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shen | NA | NA | NA | NA | 13536 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shi | NA | NA | NA | NA | 2361 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shi | NA | NA | NA | NA | 5875 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Shi | NA | NA | NA | NA | 14320 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Song | NA | NA | NA | NA | 12479 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Song | NA | NA | NA | NA | 13597 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Sun | NA | NA | NA | NA | 4863 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Sun | NA | NA | NA | NA | 9022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Sun | NA | NA | NA | NA | 12471 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Sun | NA | NA | NA | NA | 13169 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Sun | NA | NA | NA | NA | 14914 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Sun | NA | NA | NA | NA | 16041 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Tan | NA | NA | NA | NA | 8278 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Tan | NA | NA | NA | NA | 10474 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Tang | NA | NA | NA | NA | 1094 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Tang | NA | NA | NA | NA | 5983 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Tao | NA | NA | NA | NA | 3378 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Tao | NA | NA | NA | NA | 4319 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Tao | NA | NA | NA | NA | 6782 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Wan | NA | NA | NA | NA | 4052 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Wan | NA | NA | NA | NA | 4895 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Wang | NA | NA | NA | NA | 5345 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Wang | NA | NA | NA | NA | 8552 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Wei | NA | NA | NA | NA | 1743 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Wei | NA | NA | NA | NA | 1794 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Wei | NA | NA | NA | NA | 16221 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xiang | NA | NA | NA | NA | 15243 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xiang | NA | NA | NA | NA | 15328 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xie | NA | NA | NA | NA | 10881 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xie | NA | NA | NA | NA | 11986 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xie | NA | NA | NA | NA | 13774 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xu | NA | NA | NA | NA | 7689 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xu | NA | NA | NA | NA | 12363 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xue | NA | NA | NA | NA | 1178 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xue | NA | NA | NA | NA | 4181 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xue | NA | NA | NA | NA | 6179 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xue | NA | NA | NA | NA | 8073 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Xue | NA | NA | NA | NA | 13395 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yang | NA | NA | NA | NA | 3452 | NA | $HADE | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yang | NA | NA | NA | NA | 8083 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yang | NA | NA | NA | NA | 10220 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yao | NA | NA | NA | NA | 1950 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yao | NA | NA | NA | NA | 8778 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yao | NA | NA | NA | NA | 11043 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ye | NA | NA | NA | NA | 740 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Ye | NA | NA | NA | NA | 3027 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yi | NA | NA | NA | NA | 1877 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yi | NA | NA | NA | NA | 9067 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yi | NA | NA | NA | NA | 11135 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yin | NA | NA | NA | NA | 2961 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yin | NA | NA | NA | NA | 6060 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yuan | NA | NA | NA | NA | 6214 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yuan | NA | NA | NA | NA | 8646 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Yuan | NA | NA | NA | NA | 9751 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zeng | NA | NA | NA | NA | 7 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zeng | NA | NA | NA | NA | 7613 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhang | NA | NA | NA | NA | 6536 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhang | NA | NA | NA | NA | 8657 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhao | NA | NA | NA | NA | 1663 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhao | NA | NA | NA | NA | 2728 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhao | NA | NA | NA | NA | 4257 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhao | NA | NA | NA | NA | 6238 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zheng | NA | NA | NA | NA | 2097 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zheng | NA | NA | NA | NA | 3416 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zheng | NA | NA | NA | NA | 9250 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhong | NA | NA | NA | NA | 15274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhong | NA | NA | NA | NA | 16018 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhou | NA | NA | NA | NA | 3628 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhou | NA | NA | NA | NA | 9091 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhou | NA | NA | NA | NA | 15127 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhu | NA | NA | NA | NA | 3799 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zhu | NA | NA | NA | NA | 16447 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zou | NA | NA | NA | NA | 7467 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zou | NA | NA | NA | NA | 9910 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zou | NA | NA | NA | NA | 10587 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiulan Zou | NA | NA | NA | NA | 10702 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Bai | NA | NA | NA | NA | 2294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Bai | NA | NA | NA | NA | 2969 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Bai | NA | NA | NA | NA | 7046 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Bai | NA | NA | NA | NA | 12698 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cai | NA | NA | NA | NA | 3162 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cai | NA | NA | NA | NA | 4303 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cai | NA | NA | NA | NA | 13987 | NA | PRVYER | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cao | NA | NA | NA | NA | 2241 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cao | NA | NA | NA | NA | 13783 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Chang | NA | NA | NA | NA | 9074 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Chang | NA | NA | NA | NA | 10998 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cheng | NA | NA | NA | NA | 6198 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cheng | NA | NA | NA | NA | 15140 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cui | NA | NA | NA | NA | 5236 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Cui | NA | NA | NA | NA | 13375 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Dai | NA | NA | NA | NA | 1953 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Dai | NA | NA | NA | NA | 6514 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Dai | NA | NA | NA | NA | 7788 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Deng | NA | NA | NA | NA | 3265 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Deng | NA | NA | NA | NA | 3915 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Deng | NA | NA | NA | NA | 8111 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Deng | NA | NA | NA | NA | 12740 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ding | NA | NA | NA | NA | 2417 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ding | NA | NA | NA | NA | 3629 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ding | NA | NA | NA | NA | 10706 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ding | NA | NA | NA | NA | 13316 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Dong | NA | NA | NA | NA | 89 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Dong | NA | NA | NA | NA | 825 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Dong | NA | NA | NA | NA | 5027 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Dong | NA | NA | NA | NA | 7481 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Du | NA | NA | NA | NA | 3830 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Du | NA | NA | NA | NA | 9906 | NA | The Phantom Manifest | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Du | NA | NA | NA | NA | 10019 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Du | NA | NA | NA | NA | 13595 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Duan | NA | NA | NA | NA | 930 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Duan | NA | NA | NA | NA | 10408 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Duan | NA | NA | NA | NA | 16627 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Fan | NA | NA | NA | NA | 1201 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Fan | NA | NA | NA | NA | 2503 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Fan | NA | NA | NA | NA | 5196 | NA | Leo Winter | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Fan | NA | NA | NA | NA | 8109 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Gu | NA | NA | NA | NA | 2131 | NA | Monroe | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Gu | NA | NA | NA | NA | 7627 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Gu | NA | NA | NA | NA | 11755 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Gu | NA | NA | NA | NA | 11787 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Guo | NA | NA | NA | NA | 315 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Guo | NA | NA | NA | NA | 7445 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Guo | NA | NA | NA | NA | 16504 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Han | NA | NA | NA | NA | 6007 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Han | NA | NA | NA | NA | 8508 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Han | NA | NA | NA | NA | 11349 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Han | NA | NA | NA | NA | 14328 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Hou | NA | NA | NA | NA | 10647 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Hou | NA | NA | NA | NA | 10821 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Hou | NA | NA | NA | NA | 13212 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Huang | NA | NA | NA | NA | 1346 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Huang | NA | NA | NA | NA | 1627 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Huang | NA | NA | NA | NA | 6451 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Huang | NA | NA | NA | NA | 13693 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Jin | NA | NA | NA | NA | 4033 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Jin | NA | NA | NA | NA | 4695 | NA | Feral Psalm | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Jin | NA | NA | NA | NA | 15717 | NA | $ERPENT | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Kang | NA | NA | NA | NA | 1015 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Kang | NA | NA | NA | NA | 8882 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Kang | NA | NA | NA | NA | 10242 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Kong | NA | NA | NA | NA | 2033 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Kong | NA | NA | NA | NA | 4744 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Kong | NA | NA | NA | NA | 6578 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Kong | NA | NA | NA | NA | 8540 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Li | NA | NA | NA | NA | 2558 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Li | NA | NA | NA | NA | 4394 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Li | NA | NA | NA | NA | 10899 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Li | NA | NA | NA | NA | 15576 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Liang | NA | NA | NA | NA | 748 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Liang | NA | NA | NA | NA | 5050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Liao | NA | NA | NA | NA | 4977 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Liao | NA | NA | NA | NA | 8301 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Lin | NA | NA | NA | NA | 1724 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Lin | NA | NA | NA | NA | 3266 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Lin | NA | NA | NA | NA | 9907 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Lin | NA | NA | NA | NA | 10731 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Lu | NA | NA | NA | NA | 3888 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Lu | NA | NA | NA | NA | 14999 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Luo | NA | NA | NA | NA | 7412 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Luo | NA | NA | NA | NA | 11060 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ma | NA | NA | NA | NA | 6436 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ma | NA | NA | NA | NA | 13881 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Meng | NA | NA | NA | NA | 20 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Meng | NA | NA | NA | NA | 4600 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Meng | NA | NA | NA | NA | 8087 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Meng | NA | NA | NA | NA | 15905 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Meng | NA | NA | NA | NA | 16691 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Mo | NA | NA | NA | NA | 4589 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Mo | NA | NA | NA | NA | 7857 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Mo | NA | NA | NA | NA | 8716 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Mo | NA | NA | NA | NA | 9900 | NA | Veritas | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Peng | NA | NA | NA | NA | 4451 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Peng | NA | NA | NA | NA | 8684 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Peng | NA | NA | NA | NA | 10606 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Peng | NA | NA | NA | NA | 14849 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qian | NA | NA | NA | NA | 5037 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qian | NA | NA | NA | NA | 13164 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qian | NA | NA | NA | NA | 15721 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qin | NA | NA | NA | NA | 4951 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qin | NA | NA | NA | NA | 10573 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qin | NA | NA | NA | NA | 12767 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qiu | NA | NA | NA | NA | 3417 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qiu | NA | NA | NA | NA | 4042 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qiu | NA | NA | NA | NA | 4058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Qiu | NA | NA | NA | NA | 8205 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ren | NA | NA | NA | NA | 5701 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ren | NA | NA | NA | NA | 6971 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ren | NA | NA | NA | NA | 16711 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Shen | NA | NA | NA | NA | 11341 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Shen | NA | NA | NA | NA | 12786 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Shi | NA | NA | NA | NA | 9506 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Shi | NA | NA | NA | NA | 10703 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Song | NA | NA | NA | NA | 5366 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Song | NA | NA | NA | NA | 9171 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Song | NA | NA | NA | NA | 12390 | NA | Vinny Carter | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Sun | NA | NA | NA | NA | 8375 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Sun | NA | NA | NA | NA | 16619 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Tan | NA | NA | NA | NA | 12038 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Tan | NA | NA | NA | NA | 13730 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Tang | NA | NA | NA | NA | 3061 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Tang | NA | NA | NA | NA | 12506 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Tian | NA | NA | NA | NA | 3442 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Tian | NA | NA | NA | NA | 9118 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Tian | NA | NA | NA | NA | 14982 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Wan | NA | NA | NA | NA | 3838 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Wan | NA | NA | NA | NA | 15474 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Wang | NA | NA | NA | NA | 2903 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Wang | NA | NA | NA | NA | 8548 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Wang | NA | NA | NA | NA | 13458 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Wei | NA | NA | NA | NA | 9724 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Wei | NA | NA | NA | NA | 14222 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xia | NA | NA | NA | NA | 8554 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xia | NA | NA | NA | NA | 10296 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xia | NA | NA | NA | NA | 16593 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xiang | NA | NA | NA | NA | 2021 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xiang | NA | NA | NA | NA | 5249 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xiang | NA | NA | NA | NA | 5370 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xiang | NA | NA | NA | NA | 7985 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xie | NA | NA | NA | NA | 3 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xie | NA | NA | NA | NA | 3363 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xie | NA | NA | NA | NA | 15599 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xu | NA | NA | NA | NA | 10202 | NA | Onyx Rose | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xu | NA | NA | NA | NA | 11919 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xu | NA | NA | NA | NA | 16592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xue | NA | NA | NA | NA | 3280 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Xue | NA | NA | NA | NA | 16574 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yan | NA | NA | NA | NA | 9125 | NA | Tori Night | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yan | NA | NA | NA | NA | 10479 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yao | NA | NA | NA | NA | 2397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yao | NA | NA | NA | NA | 3366 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yao | NA | NA | NA | NA | 3684 | NA | Mirrored Silence | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yao | NA | NA | NA | NA | 5412 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yao | NA | NA | NA | NA | 11530 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ye | NA | NA | NA | NA | 4289 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ye | NA | NA | NA | NA | 4979 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ye | NA | NA | NA | NA | 7619 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ye | NA | NA | NA | NA | 10502 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Ye | NA | NA | NA | NA | 12257 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yin | NA | NA | NA | NA | 2566 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yin | NA | NA | NA | NA | 5103 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yin | NA | NA | NA | NA | 13162 | NA | Ivory Skyline | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yu | NA | NA | NA | NA | 2132 | NA | D.C. Rain | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yu | NA | NA | NA | NA | 7695 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yuan | NA | NA | NA | NA | 476 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yuan | NA | NA | NA | NA | 1697 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yuan | NA | NA | NA | NA | 5778 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yuan | NA | NA | NA | NA | 7846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yuan | NA | NA | NA | NA | 9398 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Yuan | NA | NA | NA | NA | 15757 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zeng | NA | NA | NA | NA | 7901 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zeng | NA | NA | NA | NA | 8279 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zeng | NA | NA | NA | NA | 8863 | NA | The Phoenix | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zeng | NA | NA | NA | NA | 10913 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zeng | NA | NA | NA | NA | 15505 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zeng | NA | NA | NA | NA | 16596 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhang | NA | NA | NA | NA | 6017 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhang | NA | NA | NA | NA | 7933 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhang | NA | NA | NA | NA | 8110 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhong | NA | NA | NA | NA | 5806 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhong | NA | NA | NA | NA | 12559 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhou | NA | NA | NA | NA | 5275 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhou | NA | NA | NA | NA | 14826 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhou | NA | NA | NA | NA | 15312 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhu | NA | NA | NA | NA | 2506 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Xiuying Zhu | NA | NA | NA | NA | 16351 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Bai | NA | NA | NA | NA | 15174 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Bai | NA | NA | NA | NA | 15774 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cai | NA | NA | NA | NA | 1219 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cai | NA | NA | NA | NA | 3035 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cao | NA | NA | NA | NA | 10148 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cao | NA | NA | NA | NA | 13082 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Chang | NA | NA | NA | NA | 7737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Chang | NA | NA | NA | NA | 12628 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Chang | NA | NA | NA | NA | 14889 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Chen | NA | NA | NA | NA | 1247 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Chen | NA | NA | NA | NA | 14147 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Chen | NA | NA | NA | NA | 16131 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cheng | NA | NA | NA | NA | 5069 | NA | Ivessa | NA | FALSE | FALSE | FALSE |
| Person | Yan Cheng | NA | NA | NA | NA | 11708 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cheng | NA | NA | NA | NA | 12306 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cui | NA | NA | NA | NA | 3610 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cui | NA | NA | NA | NA | 5533 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Cui | NA | NA | NA | NA | 12553 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Dai | NA | NA | NA | NA | 3890 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Dai | NA | NA | NA | NA | 12239 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Ding | NA | NA | NA | NA | 6383 | NA | Mystic Dawn | NA | FALSE | FALSE | FALSE |
| Person | Yan Ding | NA | NA | NA | NA | 16024 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Duan | NA | NA | NA | NA | 801 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Duan | NA | NA | NA | NA | 9251 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Fang | NA | NA | NA | NA | 5102 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Fang | NA | NA | NA | NA | 7621 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Fang | NA | NA | NA | NA | 13390 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Fang | NA | NA | NA | NA | 14812 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Feng | NA | NA | NA | NA | 88 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Feng | NA | NA | NA | NA | 2444 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Feng | NA | NA | NA | NA | 6270 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Feng | NA | NA | NA | NA | 7983 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Feng | NA | NA | NA | NA | 12449 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Fu | NA | NA | NA | NA | 12487 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Fu | NA | NA | NA | NA | 12762 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Fu | NA | NA | NA | NA | 14693 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Gao | NA | NA | NA | NA | 3263 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Gao | NA | NA | NA | NA | 6132 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Gao | NA | NA | NA | NA | 9615 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Gao | NA | NA | NA | NA | 12843 | NA | HE∆VEN | NA | FALSE | FALSE | FALSE |
| Person | Yan Gu | NA | NA | NA | NA | 10809 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Gu | NA | NA | NA | NA | 15117 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Guo | NA | NA | NA | NA | 3677 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Guo | NA | NA | NA | NA | 10671 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Guo | NA | NA | NA | NA | 13754 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Hao | NA | NA | NA | NA | 3138 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Hao | NA | NA | NA | NA | 10024 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan He | NA | NA | NA | NA | 4457 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan He | NA | NA | NA | NA | 6309 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan He | NA | NA | NA | NA | 8865 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan He | NA | NA | NA | NA | 13614 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Hou | NA | NA | NA | NA | 8157 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Hou | NA | NA | NA | NA | 10276 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Hou | NA | NA | NA | NA | 12149 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Hu | NA | NA | NA | NA | 11728 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Hu | NA | NA | NA | NA | 13979 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Jia | NA | NA | NA | NA | 241 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Jia | NA | NA | NA | NA | 5391 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Jin | NA | NA | NA | NA | 882 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Jin | NA | NA | NA | NA | 2994 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Jin | NA | NA | NA | NA | 9424 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Kang | NA | NA | NA | NA | 5395 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Kang | NA | NA | NA | NA | 5792 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Kang | NA | NA | NA | NA | 5982 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Kang | NA | NA | NA | NA | 6036 | NA | Vesper Illusion | NA | FALSE | FALSE | FALSE |
| Person | Yan Kang | NA | NA | NA | NA | 10669 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Kong | NA | NA | NA | NA | 3700 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Kong | NA | NA | NA | NA | 10926 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Kong | NA | NA | NA | NA | 16465 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lei | NA | NA | NA | NA | 1835 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lei | NA | NA | NA | NA | 12232 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lei | NA | NA | NA | NA | 15782 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Li | NA | NA | NA | NA | 10022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Li | NA | NA | NA | NA | 10147 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Li | NA | NA | NA | NA | 12167 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Li | NA | NA | NA | NA | 16569 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liang | NA | NA | NA | NA | 3427 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liang | NA | NA | NA | NA | 4145 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liang | NA | NA | NA | NA | 5106 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liang | NA | NA | NA | NA | 15240 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lin | NA | NA | NA | NA | 1912 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lin | NA | NA | NA | NA | 3488 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lin | NA | NA | NA | NA | 8985 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lin | NA | NA | NA | NA | 12690 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lin | NA | NA | NA | NA | 14190 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liu | NA | NA | NA | NA | 3866 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liu | NA | NA | NA | NA | 6598 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liu | NA | NA | NA | NA | 7442 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liu | NA | NA | NA | NA | 12682 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Liu | NA | NA | NA | NA | 14273 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Long | NA | NA | NA | NA | 1467 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Long | NA | NA | NA | NA | 7813 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Long | NA | NA | NA | NA | 12307 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lu | NA | NA | NA | NA | 4080 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lu | NA | NA | NA | NA | 9835 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lu | NA | NA | NA | NA | 12545 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Lu | NA | NA | NA | NA | 15314 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Luo | NA | NA | NA | NA | 6715 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Luo | NA | NA | NA | NA | 10900 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Luo | NA | NA | NA | NA | 12749 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Ma | NA | NA | NA | NA | 2890 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Ma | NA | NA | NA | NA | 13742 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qiao | NA | NA | NA | NA | 7095 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qiao | NA | NA | NA | NA | 13775 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qin | NA | NA | NA | NA | 1238 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qin | NA | NA | NA | NA | 9448 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qin | NA | NA | NA | NA | 13063 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qiu | NA | NA | NA | NA | 5422 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qiu | NA | NA | NA | NA | 7676 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qiu | NA | NA | NA | NA | 8296 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qiu | NA | NA | NA | NA | 12605 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Qiu | NA | NA | NA | NA | 12841 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Ren | NA | NA | NA | NA | 12315 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Ren | NA | NA | NA | NA | 15499 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Shao | NA | NA | NA | NA | 1355 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Shao | NA | NA | NA | NA | 15130 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Shi | NA | NA | NA | NA | 2544 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Shi | NA | NA | NA | NA | 3516 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Shi | NA | NA | NA | NA | 3578 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Shi | NA | NA | NA | NA | 8290 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Shi | NA | NA | NA | NA | 10174 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Song | NA | NA | NA | NA | 1463 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Song | NA | NA | NA | NA | 2846 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Su | NA | NA | NA | NA | 564 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Su | NA | NA | NA | NA | 7267 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Su | NA | NA | NA | NA | 7439 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Su | NA | NA | NA | NA | 9997 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Su | NA | NA | NA | NA | 16600 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Sun | NA | NA | NA | NA | 5379 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Sun | NA | NA | NA | NA | 8836 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tan | NA | NA | NA | NA | 1280 | NA | Atlas II | NA | FALSE | FALSE | FALSE |
| Person | Yan Tan | NA | NA | NA | NA | 5023 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tan | NA | NA | NA | NA | 14563 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tan | NA | NA | NA | NA | 15168 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tang | NA | NA | NA | NA | 456 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tang | NA | NA | NA | NA | 2400 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tang | NA | NA | NA | NA | 4045 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tao | NA | NA | NA | NA | 3785 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tao | NA | NA | NA | NA | 5829 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tian | NA | NA | NA | NA | 5025 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tian | NA | NA | NA | NA | 7272 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tian | NA | NA | NA | NA | 11252 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tian | NA | NA | NA | NA | 12604 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Tian | NA | NA | NA | NA | 15059 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wan | NA | NA | NA | NA | 5946 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wan | NA | NA | NA | NA | 9517 | NA | KR¥PTIC | NA | FALSE | FALSE | FALSE |
| Person | Yan Wang | NA | NA | NA | NA | 2395 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wang | NA | NA | NA | NA | 2776 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wang | NA | NA | NA | NA | 7256 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wang | NA | NA | NA | NA | 9743 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wen | NA | NA | NA | NA | 1396 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wen | NA | NA | NA | NA | 1662 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wu | NA | NA | NA | NA | 7011 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Wu | NA | NA | NA | NA | 7770 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xia | NA | NA | NA | NA | 4782 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xia | NA | NA | NA | NA | 16113 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiao | NA | NA | NA | NA | 1397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiao | NA | NA | NA | NA | 2340 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiao | NA | NA | NA | NA | 4081 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiao | NA | NA | NA | NA | 10592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiong | NA | NA | NA | NA | 815 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiong | NA | NA | NA | NA | 9944 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiong | NA | NA | NA | NA | 10737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiong | NA | NA | NA | NA | 15000 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xiong | NA | NA | NA | NA | 16460 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xue | NA | NA | NA | NA | 2713 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xue | NA | NA | NA | NA | 2935 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Xue | NA | NA | NA | NA | 9901 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yan | NA | NA | NA | NA | 1768 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yan | NA | NA | NA | NA | 3809 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yan | NA | NA | NA | NA | 3894 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yan | NA | NA | NA | NA | 6483 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yan | NA | NA | NA | NA | 7626 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yang | NA | NA | NA | NA | 2031 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yang | NA | NA | NA | NA | 7090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yang | NA | NA | NA | NA | 12483 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Ye | NA | NA | NA | NA | 8757 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Ye | NA | NA | NA | NA | 13963 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yin | NA | NA | NA | NA | 5805 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yin | NA | NA | NA | NA | 12035 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yu | NA | NA | NA | NA | 7119 | NA | Sasha James | NA | FALSE | FALSE | FALSE |
| Person | Yan Yu | NA | NA | NA | NA | 7817 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yuan | NA | NA | NA | NA | 94 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yuan | NA | NA | NA | NA | 5532 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yuan | NA | NA | NA | NA | 7468 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yuan | NA | NA | NA | NA | 13319 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Yuan | NA | NA | NA | NA | 15985 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhao | NA | NA | NA | NA | 3048 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhao | NA | NA | NA | NA | 5898 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhao | NA | NA | NA | NA | 14321 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhou | NA | NA | NA | NA | 6213 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhou | NA | NA | NA | NA | 7240 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhou | NA | NA | NA | NA | 7648 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhou | NA | NA | NA | NA | 10033 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhou | NA | NA | NA | NA | 15566 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhu | NA | NA | NA | NA | 13397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhu | NA | NA | NA | NA | 14046 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhu | NA | NA | NA | NA | 14625 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zhu | NA | NA | NA | NA | 16693 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zou | NA | NA | NA | NA | 1182 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zou | NA | NA | NA | NA | 2056 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zou | NA | NA | NA | NA | 12154 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yan Zou | NA | NA | NA | NA | 16591 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Bai | NA | NA | NA | NA | 1282 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Bai | NA | NA | NA | NA | 3208 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Bai | NA | NA | NA | NA | 4651 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Bai | NA | NA | NA | NA | 6813 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cai | NA | NA | NA | NA | 10006 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cai | NA | NA | NA | NA | 13782 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cao | NA | NA | NA | NA | 6294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cao | NA | NA | NA | NA | 10772 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Chang | NA | NA | NA | NA | 4456 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Chang | NA | NA | NA | NA | 7268 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Chang | NA | NA | NA | NA | 7535 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Chang | NA | NA | NA | NA | 14601 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Chang | NA | NA | NA | NA | 16609 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cheng | NA | NA | NA | NA | 7125 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cheng | NA | NA | NA | NA | 9515 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cheng | NA | NA | NA | NA | 12193 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cui | NA | NA | NA | NA | 656 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cui | NA | NA | NA | NA | 3775 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cui | NA | NA | NA | NA | 5248 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Cui | NA | NA | NA | NA | 12562 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Dai | NA | NA | NA | NA | 2058 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Dai | NA | NA | NA | NA | 6432 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Dai | NA | NA | NA | NA | 13719 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Deng | NA | NA | NA | NA | 1521 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Deng | NA | NA | NA | NA | 7524 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ding | NA | NA | NA | NA | 6936 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ding | NA | NA | NA | NA | 16188 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Dong | NA | NA | NA | NA | 4797 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Dong | NA | NA | NA | NA | 10203 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Duan | NA | NA | NA | NA | 4599 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Duan | NA | NA | NA | NA | 6937 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Duan | NA | NA | NA | NA | 9134 | NA | RAWK ST4R | NA | FALSE | FALSE | FALSE |
| Person | Yang Fan | NA | NA | NA | NA | 3215 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Fan | NA | NA | NA | NA | 3470 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Fan | NA | NA | NA | NA | 14792 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Gao | NA | NA | NA | NA | 1872 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Gao | NA | NA | NA | NA | 10569 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Gao | NA | NA | NA | NA | 13050 | NA | ZENO THA PROPHET | NA | FALSE | FALSE | FALSE |
| Person | Yang Gu | NA | NA | NA | NA | 130 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Gu | NA | NA | NA | NA | 2059 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Gu | NA | NA | NA | NA | 5329 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Gu | NA | NA | NA | NA | 14188 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Gu | NA | NA | NA | NA | 15231 | NA | Plasma Queen | NA | FALSE | FALSE | FALSE |
| Person | Yang Guo | NA | NA | NA | NA | 2425 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Guo | NA | NA | NA | NA | 7073 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang He | NA | NA | NA | NA | 3256 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang He | NA | NA | NA | NA | 3614 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang He | NA | NA | NA | NA | 8303 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang He | NA | NA | NA | NA | 12305 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang He | NA | NA | NA | NA | 14215 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Hou | NA | NA | NA | NA | 1793 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Hou | NA | NA | NA | NA | 5948 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Hou | NA | NA | NA | NA | 8879 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Hou | NA | NA | NA | NA | 9596 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Hou | NA | NA | NA | NA | 15296 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Jin | NA | NA | NA | NA | 1271 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Jin | NA | NA | NA | NA | 12544 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Kong | NA | NA | NA | NA | 2017 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Kong | NA | NA | NA | NA | 2874 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Kong | NA | NA | NA | NA | 11649 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Kong | NA | NA | NA | NA | 13138 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lai | NA | NA | NA | NA | 2176 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lai | NA | NA | NA | NA | 5447 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lai | NA | NA | NA | NA | 12707 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lei | NA | NA | NA | NA | 10884 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lei | NA | NA | NA | NA | 13175 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lei | NA | NA | NA | NA | 16076 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Li | NA | NA | NA | NA | 8128 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Li | NA | NA | NA | NA | 12509 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Liang | NA | NA | NA | NA | 3130 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Liang | NA | NA | NA | NA | 7880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Liao | NA | NA | NA | NA | 4144 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Liao | NA | NA | NA | NA | 5217 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Liao | NA | NA | NA | NA | 5523 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lin | NA | NA | NA | NA | 12714 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lin | NA | NA | NA | NA | 15112 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Liu | NA | NA | NA | NA | 2168 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Liu | NA | NA | NA | NA | 13757 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Long | NA | NA | NA | NA | 6178 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Long | NA | NA | NA | NA | 9514 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Long | NA | NA | NA | NA | 14284 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Long | NA | NA | NA | NA | 15792 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lu | NA | NA | NA | NA | 5093 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Lu | NA | NA | NA | NA | 7061 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Luo | NA | NA | NA | NA | 8720 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Luo | NA | NA | NA | NA | 9491 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Luo | NA | NA | NA | NA | 16587 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ma | NA | NA | NA | NA | 6186 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ma | NA | NA | NA | NA | 9147 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ma | NA | NA | NA | NA | 12336 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Meng | NA | NA | NA | NA | 13122 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Meng | NA | NA | NA | NA | 15236 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Mo | NA | NA | NA | NA | 4353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Mo | NA | NA | NA | NA | 4449 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Mo | NA | NA | NA | NA | 10578 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Pan | NA | NA | NA | NA | 73 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Pan | NA | NA | NA | NA | 492 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Pan | NA | NA | NA | NA | 3996 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Pan | NA | NA | NA | NA | 8701 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Pan | NA | NA | NA | NA | 12155 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Peng | NA | NA | NA | NA | 455 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Peng | NA | NA | NA | NA | 883 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Peng | NA | NA | NA | NA | 5712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Qiao | NA | NA | NA | NA | 3022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Qiao | NA | NA | NA | NA | 4153 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Qiao | NA | NA | NA | NA | 8090 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Qiu | NA | NA | NA | NA | 10989 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Qiu | NA | NA | NA | NA | 11756 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Shao | NA | NA | NA | NA | 5650 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Shao | NA | NA | NA | NA | 5734 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Song | NA | NA | NA | NA | 12168 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Song | NA | NA | NA | NA | 12381 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Su | NA | NA | NA | NA | 5901 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Su | NA | NA | NA | NA | 13918 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Tang | NA | NA | NA | NA | 1941 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Tang | NA | NA | NA | NA | 2075 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Tang | NA | NA | NA | NA | 6208 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Tang | NA | NA | NA | NA | 15858 | NA | Shadow | NA | FALSE | FALSE | FALSE |
| Person | Yang Wan | NA | NA | NA | NA | 1952 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Wan | NA | NA | NA | NA | 16116 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Wen | NA | NA | NA | NA | 7111 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Wen | NA | NA | NA | NA | 8368 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Wu | NA | NA | NA | NA | 3418 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Wu | NA | NA | NA | NA | 3992 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Wu | NA | NA | NA | NA | 7339 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Wu | NA | NA | NA | NA | 13441 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Wu | NA | NA | NA | NA | 14957 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xiang | NA | NA | NA | NA | 1329 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xiang | NA | NA | NA | NA | 11684 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xiao | NA | NA | NA | NA | 5007 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xiao | NA | NA | NA | NA | 7004 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xiao | NA | NA | NA | NA | 12351 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xie | NA | NA | NA | NA | 7904 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xie | NA | NA | NA | NA | 13753 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xie | NA | NA | NA | NA | 13938 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xu | NA | NA | NA | NA | 12680 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xu | NA | NA | NA | NA | 14923 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xue | NA | NA | NA | NA | 13283 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Xue | NA | NA | NA | NA | 15098 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yan | NA | NA | NA | NA | 2392 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yan | NA | NA | NA | NA | 7409 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yan | NA | NA | NA | NA | 16539 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yang | NA | NA | NA | NA | 2337 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yang | NA | NA | NA | NA | 6088 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yang | NA | NA | NA | NA | 10180 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yang | NA | NA | NA | NA | 11148 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ye | NA | NA | NA | NA | 2216 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ye | NA | NA | NA | NA | 2460 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ye | NA | NA | NA | NA | 11592 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ye | NA | NA | NA | NA | 15327 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Ye | NA | NA | NA | NA | 15946 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yi | NA | NA | NA | NA | 3034 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yi | NA | NA | NA | NA | 8946 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yi | NA | NA | NA | NA | 15907 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yin | NA | NA | NA | NA | 8070 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yin | NA | NA | NA | NA | 16608 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yu | NA | NA | NA | NA | 1233 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yu | NA | NA | NA | NA | 1406 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yu | NA | NA | NA | NA | 6248 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yu | NA | NA | NA | NA | 15751 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yuan | NA | NA | NA | NA | 1060 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Yuan | NA | NA | NA | NA | 1998 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zeng | NA | NA | NA | NA | 7098 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zeng | NA | NA | NA | NA | 13372 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhang | NA | NA | NA | NA | 963 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhang | NA | NA | NA | NA | 7818 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhang | NA | NA | NA | NA | 9094 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhang | NA | NA | NA | NA | 14970 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhao | NA | NA | NA | NA | 779 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhao | NA | NA | NA | NA | 2864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhao | NA | NA | NA | NA | 3883 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhao | NA | NA | NA | NA | 4124 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhao | NA | NA | NA | NA | 8253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhao | NA | NA | NA | NA | 8549 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhao | NA | NA | NA | NA | 8848 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zheng | NA | NA | NA | NA | 686 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zheng | NA | NA | NA | NA | 6849 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zheng | NA | NA | NA | NA | 12371 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zheng | NA | NA | NA | NA | 13573 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhong | NA | NA | NA | NA | 896 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhong | NA | NA | NA | NA | 5387 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhong | NA | NA | NA | NA | 6530 | NA | M.K. Ultra | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhong | NA | NA | NA | NA | 10028 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhong | NA | NA | NA | NA | 15908 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhou | NA | NA | NA | NA | 2883 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhou | NA | NA | NA | NA | 14253 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhou | NA | NA | NA | NA | 15802 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhu | NA | NA | NA | NA | 11692 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zhu | NA | NA | NA | NA | 15175 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zou | NA | NA | NA | NA | 1237 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zou | NA | NA | NA | NA | 9762 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yang Zou | NA | NA | NA | NA | 15938 | NA | Lola Fox | NA | FALSE | FALSE | FALSE |
| Person | Yong Cao | NA | NA | NA | NA | 1908 | NA | H3X MOBB | NA | FALSE | FALSE | FALSE |
| Person | Yong Cao | NA | NA | NA | NA | 6584 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Cao | NA | NA | NA | NA | 6716 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Cao | NA | NA | NA | NA | 12619 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Cao | NA | NA | NA | NA | 16694 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Chang | NA | NA | NA | NA | 1352 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Chang | NA | NA | NA | NA | 14623 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Chen | NA | NA | NA | NA | 1359 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Chen | NA | NA | NA | NA | 3196 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Chen | NA | NA | NA | NA | 6150 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Cui | NA | NA | NA | NA | 5246 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Cui | NA | NA | NA | NA | 5810 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Dai | NA | NA | NA | NA | 3713 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Dai | NA | NA | NA | NA | 12581 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Dai | NA | NA | NA | NA | 14664 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Deng | NA | NA | NA | NA | 2230 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Deng | NA | NA | NA | NA | 3827 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Deng | NA | NA | NA | NA | 14752 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Ding | NA | NA | NA | NA | 2759 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Ding | NA | NA | NA | NA | 14660 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Ding | NA | NA | NA | NA | 16181 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Dong | NA | NA | NA | NA | 1276 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Dong | NA | NA | NA | NA | 8849 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Du | NA | NA | NA | NA | 738 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Du | NA | NA | NA | NA | 5771 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Fan | NA | NA | NA | NA | 479 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Fan | NA | NA | NA | NA | 2884 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Fan | NA | NA | NA | NA | 3295 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Feng | NA | NA | NA | NA | 4616 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Feng | NA | NA | NA | NA | 13398 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Fu | NA | NA | NA | NA | 1628 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Fu | NA | NA | NA | NA | 1954 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Fu | NA | NA | NA | NA | 3900 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Fu | NA | NA | NA | NA | 6055 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Fu | NA | NA | NA | NA | 7087 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Gao | NA | NA | NA | NA | 2712 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Gao | NA | NA | NA | NA | 13505 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Gong | NA | NA | NA | NA | 3119 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Gong | NA | NA | NA | NA | 6099 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Gu | NA | NA | NA | NA | 3926 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Gu | NA | NA | NA | NA | 16474 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Guo | NA | NA | NA | NA | 9098 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Guo | NA | NA | NA | NA | 11119 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Hao | NA | NA | NA | NA | 1328 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Hao | NA | NA | NA | NA | 15445 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Hou | NA | NA | NA | NA | 7050 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Hou | NA | NA | NA | NA | 14069 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Hu | NA | NA | NA | NA | 5482 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Hu | NA | NA | NA | NA | 10375 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Hu | NA | NA | NA | NA | 12330 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Jia | NA | NA | NA | NA | 2646 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Jia | NA | NA | NA | NA | 6260 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Jia | NA | NA | NA | NA | 8124 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Jia | NA | NA | NA | NA | 8442 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Jia | NA | NA | NA | NA | 12378 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Jia | NA | NA | NA | NA | 15617 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Kong | NA | NA | NA | NA | 2010 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Kong | NA | NA | NA | NA | 6888 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lai | NA | NA | NA | NA | 1491 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lai | NA | NA | NA | NA | 10052 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lei | NA | NA | NA | NA | 5504 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lei | NA | NA | NA | NA | 6698 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lei | NA | NA | NA | NA | 8828 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lei | NA | NA | NA | NA | 11751 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lei | NA | NA | NA | NA | 15454 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Liang | NA | NA | NA | NA | 3229 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Liang | NA | NA | NA | NA | 13411 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lin | NA | NA | NA | NA | 5541 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lin | NA | NA | NA | NA | 8144 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lin | NA | NA | NA | NA | 9319 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lin | NA | NA | NA | NA | 13890 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lin | NA | NA | NA | NA | 15250 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lin | NA | NA | NA | NA | 16079 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lin | NA | NA | NA | NA | 16737 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lu | NA | NA | NA | NA | 1336 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lu | NA | NA | NA | NA | 6759 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Lu | NA | NA | NA | NA | 11748 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Mao | NA | NA | NA | NA | 2310 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Mao | NA | NA | NA | NA | 3945 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Mao | NA | NA | NA | NA | 5408 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Meng | NA | NA | NA | NA | 2278 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Meng | NA | NA | NA | NA | 5271 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Meng | NA | NA | NA | NA | 9320 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Qian | NA | NA | NA | NA | 4325 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Qian | NA | NA | NA | NA | 7916 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Qiao | NA | NA | NA | NA | 15371 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Qiao | NA | NA | NA | NA | 16199 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Qiu | NA | NA | NA | NA | 8141 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Qiu | NA | NA | NA | NA | 8505 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Qiu | NA | NA | NA | NA | 14953 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Shen | NA | NA | NA | NA | 1490 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Shen | NA | NA | NA | NA | 3397 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Shen | NA | NA | NA | NA | 9812 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Shen | NA | NA | NA | NA | 14087 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Su | NA | NA | NA | NA | 778 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Su | NA | NA | NA | NA | 5362 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Su | NA | NA | NA | NA | 7047 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Su | NA | NA | NA | NA | 9964 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Su | NA | NA | NA | NA | 13056 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Sun | NA | NA | NA | NA | 3396 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Sun | NA | NA | NA | NA | 11170 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Sun | NA | NA | NA | NA | 14770 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tan | NA | NA | NA | NA | 2570 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tan | NA | NA | NA | NA | 3784 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tan | NA | NA | NA | NA | 12283 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tan | NA | NA | NA | NA | 14642 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tang | NA | NA | NA | NA | 2353 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tang | NA | NA | NA | NA | 9138 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tang | NA | NA | NA | NA | 11070 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tang | NA | NA | NA | NA | 11581 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tang | NA | NA | NA | NA | 16280 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tao | NA | NA | NA | NA | 3461 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tao | NA | NA | NA | NA | 8831 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tian | NA | NA | NA | NA | 1464 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tian | NA | NA | NA | NA | 11204 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Tian | NA | NA | NA | NA | 14323 | NA | Trey Lawson | NA | FALSE | FALSE | FALSE |
| Person | Yong Wei | NA | NA | NA | NA | 3294 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Wei | NA | NA | NA | NA | 12404 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Wei | NA | NA | NA | NA | 13683 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Wei | NA | NA | NA | NA | 13803 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Wen | NA | NA | NA | NA | 2613 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Wen | NA | NA | NA | NA | 6067 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Wu | NA | NA | NA | NA | 3121 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Wu | NA | NA | NA | NA | 8457 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Xia | NA | NA | NA | NA | 5147 | NA | Neon Solstice | NA | FALSE | FALSE | FALSE |
| Person | Yong Xia | NA | NA | NA | NA | 7182 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Xia | NA | NA | NA | NA | 16461 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Xue | NA | NA | NA | NA | 2611 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Xue | NA | NA | NA | NA | 10603 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Xue | NA | NA | NA | NA | 15211 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yan | NA | NA | NA | NA | 6627 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yan | NA | NA | NA | NA | 7609 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yan | NA | NA | NA | NA | 14565 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yan | NA | NA | NA | NA | 15180 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yang | NA | NA | NA | NA | 12995 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yang | NA | NA | NA | NA | 15470 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yao | NA | NA | NA | NA | 362 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yao | NA | NA | NA | NA | 4171 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yao | NA | NA | NA | NA | 10758 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Ye | NA | NA | NA | NA | 7122 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Ye | NA | NA | NA | NA | 7151 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yi | NA | NA | NA | NA | 12 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yi | NA | NA | NA | NA | 2144 | NA | YNG LUX | NA | FALSE | FALSE | FALSE |
| Person | Yong Yi | NA | NA | NA | NA | 10911 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yu | NA | NA | NA | NA | 98 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Yu | NA | NA | NA | NA | 1645 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zeng | NA | NA | NA | NA | 4146 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zeng | NA | NA | NA | NA | 11950 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zeng | NA | NA | NA | NA | 16098 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhang | NA | NA | NA | NA | 1621 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhang | NA | NA | NA | NA | 2140 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhang | NA | NA | NA | NA | 2880 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhang | NA | NA | NA | NA | 16258 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zheng | NA | NA | NA | NA | 697 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zheng | NA | NA | NA | NA | 8085 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zheng | NA | NA | NA | NA | 15697 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhong | NA | NA | NA | NA | 5501 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhong | NA | NA | NA | NA | 8616 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhong | NA | NA | NA | NA | 14183 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhou | NA | NA | NA | NA | 5070 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhou | NA | NA | NA | NA | 8769 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhu | NA | NA | NA | NA | 5022 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhu | NA | NA | NA | NA | 7622 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zhu | NA | NA | NA | NA | 10146 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zou | NA | NA | NA | NA | 2857 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zou | NA | NA | NA | NA | 11274 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yong Zou | NA | NA | NA | NA | 15864 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yumiko Ito | NA | NA | NA | NA | 526 | NA | NA | NA | FALSE | FALSE | FALSE |
| Person | Yumiko Ito | NA | NA | NA | NA | 1556 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Zenith Records | NA | NA | NA | NA | 837 | NA | NA | NA | FALSE | FALSE | FALSE |
| RecordLabel | Zenith Records | NA | NA | NA | NA | 17378 | NA | NA | NA | FALSE | FALSE | FALSE |
The following code chunk will tag each row with a unique key (group_key) based on its respective column values. This helps to identify unique records.
Show Code
mc1_nodes_tagged <- mc1_nodes_raw %>%
mutate(group_key = paste(`Node Type`, name, single, release_date, genre,
notable, written_date, notoriety_date, is_sailor,
is_oceanus_folk, sep = "|"))
kable(head(mc1_nodes_tagged,5))| Node Type | name | single | release_date | genre | notable | id | written_date | stage_name | notoriety_date | is_sailor | is_ivy | is_oceanus_folk | group_key |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Song | Breaking These Chains | TRUE | 2017 | Oceanus Folk | TRUE | 0 | NA | NA | NA | FALSE | FALSE | TRUE | Song|Breaking These Chains|TRUE|2017|Oceanus Folk|TRUE|NA|NA|FALSE|TRUE |
| Person | Carlos Duffy | NA | NA | NA | NA | 1 | NA | NA | NA | FALSE | FALSE | FALSE | Person|Carlos Duffy|NA|NA|NA|NA|NA|NA|FALSE|FALSE |
| Person | Min Qin | NA | NA | NA | NA | 2 | NA | NA | NA | FALSE | FALSE | FALSE | Person|Min Qin|NA|NA|NA|NA|NA|NA|FALSE|FALSE |
| Person | Xiuying Xie | NA | NA | NA | NA | 3 | NA | NA | NA | FALSE | FALSE | FALSE | Person|Xiuying Xie|NA|NA|NA|NA|NA|NA|FALSE|FALSE |
| RecordLabel | Nautical Mile Records | NA | NA | NA | NA | 4 | NA | NA | NA | FALSE | FALSE | FALSE | RecordLabel|Nautical Mile Records|NA|NA|NA|NA|NA|NA|FALSE|FALSE |
The code below deduplicates the dataset using group_key, reducing the number of duplicated names from 4,953 to 14. The remaining 14 names appear more than once because their corresponding records differ in at least one column used to form group_key, so they are retained as distinct entries.
Show Code
# Step 2: De-duplicate and keep the preferred (with stage_name if available)
mc1_nodes_dedup <- mc1_nodes_tagged %>%
group_by(group_key) %>%
arrange(desc(!is.na(stage_name))) %>%
slice(1) %>%
ungroup()
duplicated_name <- mc1_nodes_dedup %>%
count(name) %>%
filter(n > 1)
mc1_nodes_dedup %>%
filter(name %in% duplicated_name$name) %>%
arrange(name) %>%
kable() %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "200px")| Node Type | name | single | release_date | genre | notable | id | written_date | stage_name | notoriety_date | is_sailor | is_ivy | is_oceanus_folk | group_key |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Song | Ancestral Echoes | FALSE | 2039 | Avant-Garde Folk | TRUE | 17133 | NA | NA | NA | FALSE | FALSE | FALSE | Song|Ancestral Echoes|FALSE|2039|Avant-Garde Folk|TRUE|NA|NA|FALSE|FALSE |
| Song | Ancestral Echoes | TRUE | 1991 | Dream Pop | FALSE | 11793 | NA | NA | NA | FALSE | FALSE | FALSE | Song|Ancestral Echoes|TRUE|1991|Dream Pop|FALSE|NA|NA|FALSE|FALSE |
| Album | Coastal Echoes | NA | 2023 | Psychedelic Rock | TRUE | 15065 | 2019 | NA | 2039 | FALSE | FALSE | FALSE | Album|Coastal Echoes|NA|2023|Psychedelic Rock|TRUE|2019|2039|FALSE|FALSE |
| RecordLabel | Coastal Echoes | NA | NA | NA | NA | 4022 | NA | NA | NA | FALSE | FALSE | FALSE | RecordLabel|Coastal Echoes|NA|NA|NA|NA|NA|NA|FALSE|FALSE |
| Song | Postcards from Nowhere | FALSE | 1984 | Acoustic Folk | FALSE | 17214 | NA | NA | NA | FALSE | FALSE | FALSE | Song|Postcards from Nowhere|FALSE|1984|Acoustic Folk|FALSE|NA|NA|FALSE|FALSE |
| Song | Postcards from Nowhere | TRUE | 2023 | Indie Folk | TRUE | 12852 | 2023 | NA | NA | FALSE | FALSE | FALSE | Song|Postcards from Nowhere|TRUE|2023|Indie Folk|TRUE|2023|NA|FALSE|FALSE |
| Album | Shattered Reflections | NA | 2013 | Emo/Pop Punk | TRUE | 3325 | 2013 | NA | 2013 | FALSE | FALSE | FALSE | Album|Shattered Reflections|NA|2013|Emo/Pop Punk|TRUE|2013|2013|FALSE|FALSE |
| Song | Shattered Reflections | FALSE | 2036 | Darkwave | TRUE | 17088 | NA | NA | NA | FALSE | FALSE | FALSE | Song|Shattered Reflections|FALSE|2036|Darkwave|TRUE|NA|NA|FALSE|FALSE |
| RecordLabel | Unheard Frequencies | NA | NA | NA | NA | 10952 | NA | NA | NA | FALSE | FALSE | FALSE | RecordLabel|Unheard Frequencies|NA|NA|NA|NA|NA|NA|FALSE|FALSE |
| Song | Unheard Frequencies | TRUE | 2025 | Alternative Rock | TRUE | 7999 | NA | NA | NA | FALSE | FALSE | FALSE | Song|Unheard Frequencies|TRUE|2025|Alternative Rock|TRUE|NA|NA|FALSE|FALSE |
| Song | Vanishing Point | FALSE | 2013 | Oceanus Folk | FALSE | 17338 | NA | NA | NA | FALSE | FALSE | TRUE | Song|Vanishing Point|FALSE|2013|Oceanus Folk|FALSE|NA|NA|FALSE|TRUE |
| Song | Vanishing Point | TRUE | 2018 | Avant-Garde Folk | TRUE | 9371 | 2018 | NA | NA | FALSE | FALSE | FALSE | Song|Vanishing Point|TRUE|2018|Avant-Garde Folk|TRUE|2018|NA|FALSE|FALSE |
| Album | Vertical Horizon | NA | 2017 | Doom Metal | TRUE | 9262 | NA | NA | NA | FALSE | FALSE | FALSE | Album|Vertical Horizon|NA|2017|Doom Metal|TRUE|NA|NA|FALSE|FALSE |
| RecordLabel | Vertical Horizon | NA | NA | NA | NA | 2453 | NA | NA | NA | FALSE | FALSE | FALSE | RecordLabel|Vertical Horizon|NA|NA|NA|NA|NA|NA|FALSE|FALSE |
2.5.2 Duplicates in Edges
For Edges, there are duplicates but only their key are different. Since, information on key is not provided by VAST 2025 MC1, its purpose cannot be determined. Therefore, the key column will be redundant and duplicated edges differing only by their key will be removed.
Show Code
# Step 1: Identify duplicate combinations
duplicate_summary <- mc1_edges_raw %>%
count(source, target, `Edge Type`) %>%
filter(n > 1)
# Step 2: Join back to get all original duplicate rows
mc1_edges_raw %>%
inner_join(duplicate_summary, by = c("source", "target", "Edge Type")) %>%
kable()| Edge Type | source | target | key | n |
|---|---|---|---|---|
| PerformerOf | 17057 | 17058 | 0 | 2 |
| PerformerOf | 17057 | 17058 | 1 | 2 |
| PerformerOf | 17349 | 17350 | 0 | 2 |
| PerformerOf | 17349 | 17350 | 2 | 2 |
| PerformerOf | 17355 | 17356 | 0 | 2 |
| PerformerOf | 17355 | 17356 | 2 | 2 |
All duplicates are removed using the code below and a check was performed to show that no duplicated edges remains.
Show Code
mc1_edges_raw <- mc1_edges_raw %>%
distinct(source, target, `Edge Type`, .keep_all = TRUE) %>%
select(!key)
mc1_edges_raw %>%
count(source, target, `Edge Type`) %>%
filter(n > 1)# A tibble: 0 × 4
# ℹ 4 variables: source <int>, target <int>, Edge Type <chr>, n <int>2.6 Check Nodes and Edges range
The source and target columns seems to refer to the id column in nodes. The code below is used to confirm this assumption since they have the same range.
Show Code
range(mc1_nodes_dedup$id)[1] 0 17411Show Code
range(mc1_edges_raw$source)[1] 0 17411Show Code
range(mc1_edges_raw$target)[1] 0 174112.7 Mapping Node name to Edges id
tidygraph uses from and to columns to reference nodes. By default, tidygraph matches these edges reference against the first column in the nodes table, or against name column.
Currently, source and target columns in mc1_edges_raw contain id values that correspond to the id column in mc1_nodes_clean. To properly integrate with tidygraph’s conventions, the following will be done:
- Restructure mc1_nodes_clean
- Rename the current name column to node_name - this is done to preserve the actual node names
- Rename the id column to name so it becomes the primary identifier column that tidygraph will use for matching
- Rename source and target columns in mc1_edges_raw, as required by tidygraph
- Ensure data type consistency: Convert the name column (formerly id) to character format to match the data type of the edge references
Show Code
mc1_nodes_clean <- mc1_nodes_dedup %>%
rename(node_name = name, name = id) %>%
mutate(name = as.character(name)) %>%
select(`Node Type`, node_name, release_date, genre, notable, name, single, written_date, stage_name, notoriety_date, is_sailor, is_ivy, is_oceanus_folk)
kable(head(mc1_nodes_clean,5))| Node Type | node_name | release_date | genre | notable | name | single | written_date | stage_name | notoriety_date | is_sailor | is_ivy | is_oceanus_folk |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Album | A Lush Dystopia | 2031 | Psychedelic Rock | TRUE | 17005 | NA | 2030 | NA | NA | FALSE | FALSE | FALSE |
| Album | Addicted to Your Heartache | 2004 | Southern Gothic Rock | TRUE | 14658 | NA | 2000 | NA | NA | FALSE | FALSE | FALSE |
| Album | Adriatic Empress | 2013 | Post-Apocalyptic Folk | TRUE | 10412 | NA | NA | NA | NA | FALSE | FALSE | FALSE |
| Album | Aerial Echoes of Freedom | 2023 | Indie Rock | TRUE | 7908 | NA | NA | NA | NA | FALSE | FALSE | FALSE |
| Album | Aftershock Silence | 2028 | Dream Pop | TRUE | 2030 | NA | 2021 | NA | NA | FALSE | FALSE | FALSE |
2.7.1 Create Edge Mapping from original id to kept id
In section 3.3.2, duplicated nodes were deduplicated and removed, edges referring to the removed nodes will become invalid thus, edges will be remapped to the retained nodes. This step ensures that all edges correctly point to existing nodes in the deduplicated graph.
The code below maps the original_id to the kept_id in preparation for the next step.
Show Code
# Step 1: Create mapping of all group_key → kept id
key_to_id_map <- mc1_nodes_dedup %>%
select(group_key, kept_id = id)
# Step 2: Map all original rows to the retained ID
id_remap <- mc1_nodes_tagged %>%
left_join(key_to_id_map, by = "group_key") %>%
select(original_id = id, kept_id)
kable(head(id_remap,5))| original_id | kept_id |
|---|---|
| 0 | 0 |
| 1 | 1 |
| 2 | 14470 |
| 3 | 3 |
| 4 | 4 |
This step adds the kept_id column to the edge data.
Show Code
# Step 3: Replace edges' source and target with mapped kept_id
mc1_edges_mapped <- mc1_edges_raw %>%
left_join(id_remap, by = c("source" = "original_id"))
kable(head(mc1_edges_mapped,5))| Edge Type | source | target | kept_id |
|---|---|---|---|
| InterpolatesFrom | 0 | 1841 | 0 |
| RecordedBy | 0 | 4 | 0 |
| PerformerOf | 1 | 0 | 1 |
| ComposerOf | 1 | 16180 | 1 |
| PerformerOf | 2 | 0 | 14470 |
Next, the source is replaced by the kept_id. This is also repeated for target.
Lastly, the source and target columns are then renamed from and to respectively to follow tidygraph syntax.
Show Code
mc1_edges_mapped <- mc1_edges_mapped %>%
mutate(source = kept_id) %>%
select(-kept_id) %>%
left_join(id_remap, by = c("target" = "original_id")) %>%
mutate(target = kept_id) %>%
select(-kept_id) %>%
rename(from = source, to = target) %>%
mutate(from = as.character(from), to = as.character(to))
kable(head(mc1_edges_mapped,5))| Edge Type | from | to |
|---|---|---|
| InterpolatesFrom | 0 | 1841 |
| RecordedBy | 0 | 4 |
| PerformerOf | 1 | 0 |
| ComposerOf | 1 | 16180 |
| PerformerOf | 14470 | 0 |
2.8 Remove unmatched (invalid) edges
The following code chunk removes edges that reference missing node id, ensuring that only valid edges are kept.
Show Code
mc1_edges_clean <- mc1_edges_mapped %>%
filter(!is.na(from), !is.na(to))There are no unmatched edges.
2.9 Check for any missing nodes
This steps looks for any unmatched nodes and edges and the result shows that all nodes have matching edges and vice versa.
Show Code
setdiff(
unique(c(mc1_edges_clean$from, mc1_edges_clean$to)),
mc1_nodes_clean$name
)character(0)2.10 Checking Edges Schema
This section aims to ensure that each edge in the graph adheres to the schema specified in the VAST Challenge 2025 MC1 Data Description document. The following code checks whether the node types connect by each edge matches the valid source and target types for that edge’s type.
Show Code
# Define valid source and destination types for each edge type
edge_rules <- list(
PerformerOf = list(source = c("Person", "MusicalGroup"), target = c("Song", "Album")),
ComposerOf = list(source = c("Person"), target = c("Song", "Album")),
ProducerOf = list(source = c("Person", "RecordLabel"), target = c("Song", "Album", "Person", "MusicalGroup")),
LyricistOf = list(source = c("Person"), target = c("Song", "Album")),
RecordedBy = list(source = c("Song", "Album"), target = c("RecordLabel")),
DistributedBy = list(source = c("Song", "Album"), target = c("RecordLabel")),
InStyleOf = list(source = c("Song", "Album"), target = c("Song", "Album", "Person", "MusicalGroup")),
InterpolatesFrom = list(source = c("Song", "Album"), target = c("Song", "Album")),
CoverOf = list(source = c("Song", "Album"), target = c("Song", "Album")),
LyricalReferenceTo = list(source = c("Song", "Album"), target = c("Song", "Album")),
DirectlySamples = list(source = c("Song", "Album"), target = c("Song", "Album")),
MemberOf = list(source = c("Person"), target = c("MusicalGroup"))
)Using the rules defined above, the code below checks for erroneous edge and node relationships and shows that there are multiple invalid edges.
Show Code
# Create a lookup for node types
node_type_lookup <- mc1_nodes_clean %>%
select(name, `Node Type`) %>%
deframe()
# Add source and target node types to the edge table
mc1_edges_checked <- mc1_edges_clean %>%
mutate(
source_type = node_type_lookup[from],
target_type = node_type_lookup[to]
)
mc1_edges_tagged <- mc1_edges_checked %>%
rowwise() %>%
mutate(
valid = {
rule <- edge_rules[[`Edge Type`]]
if (is.null(rule)) TRUE
else {
source_type %in% rule$source && target_type %in% rule$target
}
}
) %>%
ungroup()
# Count and display invalid edge combinations
invalid_edge_summary <- mc1_edges_tagged %>%
filter(!valid) %>%
count(`Edge Type`, source_type, target_type, sort = TRUE)
kable(head(invalid_edge_summary,5))| Edge Type | source_type | target_type | n |
|---|---|---|---|
| LyricistOf | MusicalGroup | Song | 106 |
| RecordedBy | RecordLabel | Album | 102 |
| ProducerOf | MusicalGroup | Song | 100 |
| ComposerOf | MusicalGroup | Song | 97 |
| ProducerOf | MusicalGroup | Album | 31 |
In total, there are 550 invalid edges.
Show Code
# Check total invalid edge count
cat("Total invalid edges:", sum(!mc1_edges_tagged$valid), "\n")Total invalid edges: 550 Finally, the invalid edges are removed.
Show Code
# Keep only valid edges
mc1_edges_clean <- mc1_edges_tagged %>%
filter(valid)
cat("Total invalid edges:", sum(!mc1_edges_clean$valid), "\n")Total invalid edges: 0 Show Code
mc1_edges_clean <- mc1_edges_clean %>%
select(from, to, `Edge Type`) # drop helper columns2.11 Temporal Validation
The following code chunk is used to ensure any influenced songs/albums are not released before the songs/albums that influenced them. If there are any of such cases, it will be flagged out.
# Define which edge types represent influence relationships between songs/albums
influence_edge_types <- c("InStyleOf", "InterpolatesFrom", "CoverOf",
"LyricalReferenceTo", "DirectlySamples")
# Check for temporal inconsistencies in song/album influence relationships
temporal_check <- mc1_edges_clean %>%
# Focus only on influence edge types
filter(`Edge Type` %in% influence_edge_types) %>%
# Add source node info (the influenced song/album)
left_join(mc1_nodes_clean %>%
select(name, source_type = `Node Type`, source_release = release_date),
by = c("from" = "name")) %>%
# Add target node info (the influencer song/album)
left_join(mc1_nodes_clean %>%
select(name, target_type = `Node Type`, target_release = release_date),
by = c("to" = "name")) %>%
# Only check Song/Album -> Song/Album relationships
filter(source_type %in% c("Song", "Album"),
target_type %in% c("Song", "Album")) %>%
# Check for temporal violations
mutate(
temporal_violation = case_when(
is.na(source_release) | is.na(target_release) ~ FALSE, # Skip if dates missing
source_release < target_release ~ TRUE, # Influenced before influencer
TRUE ~ FALSE
)
)
# Summary of temporal violations
violation_summary <- temporal_check %>%
filter(temporal_violation) %>%
count(`Edge Type`, sort = TRUE)
kable(head(violation_summary))| Edge Type | n |
|---|---|
| InStyleOf | 28 |
| LyricalReferenceTo | 19 |
| CoverOf | 17 |
| InterpolatesFrom | 15 |
| DirectlySamples | 5 |
These are the invalid cases where the target works (e.g. songs) influencing the source works were released after the source works.
# Show examples of violations with node names
violation_examples <- temporal_check %>%
filter(temporal_violation) %>%
left_join(mc1_nodes_clean %>% select(name, source_name = node_name),
by = c("from" = "name")) %>%
left_join(mc1_nodes_clean %>% select(name, target_name = node_name),
by = c("to" = "name")) %>%
select(source_name, target_name, `Edge Type`, source_release, target_release) %>%
arrange(source_release)
kable(head(violation_examples,5))| source_name | target_name | Edge Type | source_release | target_release |
|---|---|---|---|---|
| Sacred Invocation | The Calm Chorus | CoverOf | 1987 | 1989 |
| Lucifer’s Rhythm | Whispers of Self-Destruction | CoverOf | 1994 | 1996 |
| The Ballad of Billy’s Bravado | Resilience of the Spirit | InterpolatesFrom | 1997 | 2000 |
| Salt and Silence | Mercy’s Melody | InStyleOf | 1997 | 1999 |
| Culloden’s Lament | Shattered Pieces | InterpolatesFrom | 1998 | 2000 |
A check was done on the influenced works and their release dates.
total_violations <- sum(temporal_check$temporal_violation, na.rm = TRUE)
total_checked <- nrow(temporal_check)
cat("\nTotal song/album influence relationships checked:", total_checked, "\n")
Total song/album influence relationships checked: 7340 cat("Total temporal violations found:", total_violations, "\n")Total temporal violations found: 84 2.11.1 Removing all edges that have temporal issues
The following code chunk will remove all edges which was highlighted in Section 3.8 that has violated the temporal influence.
# Get all edges that are not influence relationships (keep as-is)
non_influence_edges <- mc1_edges_clean %>%
filter(!(`Edge Type` %in% influence_edge_types))
# Get temporally consistent influence edges
consistent_influence_edges <- temporal_check %>%
filter(!temporal_violation) %>%
select(from, to, `Edge Type`)
# Combine all valid edges
mc1_edges_clean <- bind_rows(non_influence_edges, consistent_influence_edges)total_cleaned_influences <- consistent_influence_edges %>% nrow()
cat("Total song/album influence relationships after cleaning:", total_cleaned_influences, "\n")Total song/album influence relationships after cleaning: 7256 2.12 Check for orphan nodes
# Get all node IDs that appear in edges (either as source or target)
nodes_with_edges <- unique(c(mc1_edges_clean$from, mc1_edges_clean$to))
# Find nodes that don't appear in any edges
orphan_nodes <- mc1_nodes_clean %>%
filter(!name %in% nodes_with_edges)
# Summary of orphan nodes
cat("Total nodes:", nrow(mc1_nodes_clean), "\n")Total nodes: 14077 cat("Nodes with edges:", length(nodes_with_edges), "\n")Nodes with edges: 14077 cat("Orphan nodes (no edges):", nrow(orphan_nodes), "\n")Orphan nodes (no edges): 0 2.13 Creating Consistent Visualisation Colouring
The code below groups different types of edges and nodes into broader categories for consistent visualisation colouring.
Show Code
mc1_edges_clean <- mc1_edges_clean %>%
mutate(`Edge Colour` = case_when(
`Edge Type` %in% c("PerformerOf", "ComposerOf", "ProducerOf", "LyricistOf", "RecordedBy", "DistributedBy") ~ "Creator Of",
`Edge Type` %in% c("InStyleOf", "InterpolatesFrom", "CoverOf", "LyricalReferenceTo", "DirectlySamples") ~ "Influenced By",
`Edge Type` == "MemberOf" ~ "Member Of",
TRUE ~ "Other"
))
mc1_nodes_clean <- mc1_nodes_clean %>%
mutate(
`Node Colour` = case_when(
`Node Type` %in% c("Person", "MusicalGroup", "RecordLabel") ~ "Musician",
genre == "Oceanus Folk" ~ "Oceanus Folk",
TRUE ~ "Other Genre"
)
)2.14 Creating the Global Knowledge Graph
The code below uses tbl_graph() to create a tidygraph’s graph object.
Show Code
graph = tbl_graph(edges = mc1_edges_clean,
nodes = mc1_nodes_clean,
directed = TRUE)Since several of the ggraph layouts involve randomisation, this code sets the seed value to ensure reproducibility of all the plots.
Show Code
set.seed(1234)3 Exploratory Data Analysis (EDA) on Sailor Shift’s career
We will design and develop visualizations and visual analytic tools that will allow Silas to explore and understand the profile of Sailor Shift’s career.
Note
This analysis examines Sailor Shift’s work during her solo artist career, excluding her initial collaborative period with Ivy Echos.
Future work: What if we make everything into a function and find members that the person is part of and use a while loop to get everything so it includes all groups that the person is a part of?
3.1 Visualising Sailor Shift’s Music
The analysis begins by extracting Sailor Shift’s name from the node dataset. Following this, all outgoing edges originating from her node are identified. The resulting nodes from those edges are filtered to isolate only those classified as Songs and Albums, thereby displaying her musical career.
Show Code
# Step 0: Get name of 'Sailor Shift'
sailor_vertex_name <- mc1_nodes_clean %>%
filter(is_sailor == TRUE) %>%
pull(name)
# Step 1: Find outgoing edges from Sailor Shift
sailor_out_edges <- mc1_edges_clean %>%
filter(from == sailor_vertex_name)
# Step 2: Identify neighbour node names
sailor_out_node_names <- sailor_out_edges$to
# Step 4: Identify songs/albums
sailor_music_all <- mc1_nodes_clean %>%
filter(name %in% sailor_out_node_names, `Node Type` %in% c("Song", "Album")) %>%
pull(name)
# Step 5: Build subgraph using names
sub_nodes <- unique(c(sailor_vertex_name, sailor_music_all))
sub_graph <- graph %>%
activate(nodes) %>%
filter(name %in% sub_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name %in% c("Sailor Shift", "Ivy Echos", "Wei Zhao"), 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == "Sailor Shift", "Sailor Shift",
ifelse(node_name == "Ivy Echos", "Ivy Echos",
ifelse(node_name == "Wei Zhao", "Wei Zhao", NA)))
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)
Sailor Shift’s Music Insights
- In total, Sailor Shift released 38 Songs and Albums from 2024 to 2040
- Details on the Songs and Albums can be found in the table below
- Sailor Shift released 4 Songs in 2028
- Among those, only 1 is a Single
- Therefore, the viral Song that spark her breakthrough is High Tide Heartbeat
- Among her Songs and Albums, 36 belong to the Oceanus Folk genre, while there is 1 Americana and 1 Synthwave Album each.
Show Code
mc1_nodes_clean %>%
filter(name %in% sailor_music_all) %>%
arrange(release_date) %>%
select(`Node Type`, node_name, release_date, genre, notable, single, notoriety_date) %>%
kable() %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "300px")| Node Type | node_name | release_date | genre | notable | single | notoriety_date |
|---|---|---|---|---|---|---|
| Album | The Kelp Forest Canticles | 2024 | Oceanus Folk | TRUE | NA | NA |
| Album | Luminescent Tides | 2025 | Oceanus Folk | TRUE | NA | NA |
| Album | Shoreline Sonnets | 2026 | Oceanus Folk | TRUE | NA | NA |
| Album | Tidal Pop Waves | 2028 | Oceanus Folk | TRUE | NA | NA |
| Song | Chord of the Deep | 2028 | Oceanus Folk | FALSE | FALSE | NA |
| Song | Electric Eel Love | 2028 | Oceanus Folk | TRUE | FALSE | NA |
| Song | High Tide Heartbeat | 2028 | Oceanus Folk | FALSE | TRUE | NA |
| Song | Sun-Drenched Daydream | 2028 | Oceanus Folk | FALSE | FALSE | NA |
| Album | Tides of Echos | 2029 | Oceanus Folk | TRUE | NA | NA |
| Album | Salty Dreams | 2030 | Oceanus Folk | TRUE | NA | NA |
| Song | Driftwood Lullaby | 2030 | Oceanus Folk | FALSE | FALSE | NA |
| Song | Heart of the Habitat | 2030 | Oceanus Folk | FALSE | TRUE | NA |
| Song | Reef Rhythm | 2030 | Oceanus Folk | FALSE | FALSE | NA |
| Song | Seashell Serenade | 2030 | Oceanus Folk | TRUE | TRUE | 2030 |
| Album | Hidden Depths | 2031 | Oceanus Folk | TRUE | NA | NA |
| Album | Neon Heartbeat | 2031 | Synthwave | FALSE | NA | NA |
| Album | Submerged Sonatas | 2031 | Oceanus Folk | TRUE | NA | NA |
| Album | Tidesworn Ballads | 2031 | Oceanus Folk | TRUE | NA | NA |
| Album | The Current & The Chord | 2032 | Oceanus Folk | TRUE | NA | NA |
| Song | Saltwater Hymn | 2032 | Oceanus Folk | FALSE | FALSE | NA |
| Album | Ballads for the End of Time | 2033 | Oceanus Folk | TRUE | NA | NA |
| Album | Melancholy Circuitry | 2033 | Americana | TRUE | NA | NA |
| Album | Coral Beats | 2034 | Oceanus Folk | TRUE | NA | NA |
| Album | Drifting Between the Stars and the Sea | 2034 | Oceanus Folk | TRUE | NA | NA |
| Song | Barnacle Heart | 2034 | Oceanus Folk | FALSE | FALSE | NA |
| Song | Into the Current | 2034 | Oceanus Folk | FALSE | TRUE | NA |
| Song | Moon Over the Tide | 2034 | Oceanus Folk | TRUE | FALSE | NA |
| Album | Artificial Sunsets | 2035 | Oceanus Folk | TRUE | NA | NA |
| Album | Tides & Ballads | 2036 | Oceanus Folk | TRUE | NA | NA |
| Song | Fog & Fiddle | 2036 | Oceanus Folk | TRUE | FALSE | NA |
| Song | The Fisherman's Prayer | 2036 | Oceanus Folk | FALSE | TRUE | NA |
| Album | Ballads for the Low Tide | 2037 | Oceanus Folk | TRUE | NA | NA |
| Album | Electric Reverie | 2038 | Oceanus Folk | TRUE | NA | NA |
| Album | Oceanbound | 2038 | Oceanus Folk | TRUE | NA | NA |
| Song | Stormsong | 2038 | Oceanus Folk | TRUE | TRUE | NA |
| Album | Echoes of the Deep | 2040 | Oceanus Folk | TRUE | NA | NA |
| Song | Salt in My Veins | 2040 | Oceanus Folk | FALSE | FALSE | NA |
| Song | The Last Mariner | 2040 | Oceanus Folk | FALSE | FALSE | NA |
4.2 Question 1a) Who has she been most influenced by over time?
This section is a continuation from the previous section where all her outgoing edges were found. Music that she produced were already found and now Persons and Musical Groups that are outgoing from her are included. From these Songs, Albums, Persons and Musical Groups, only those Songs and Albums with further outgoing edges are kept. Then, the nodes connected to those are found. These are music that her music have been influenced by. Finally, the last step finds Person and Musical Groups who produced the music that have influenced her music.
Note: The term music refers to either Song or Album.
Show Code
# Data Preparation
# Step 1: Get all creator names
global_creators <- mc1_nodes_clean %>%
filter(`Node Type` %in% c("Person", "MusicalGroup"))
# Step 2: Get all outgoing edges from these creators
creator_out_edges <- mc1_edges_clean %>%
filter(from %in% global_creators$name, `Edge Colour` == "Creator Of")
# Step 3: Get all songs made by creators
creator_music <- mc1_nodes_clean %>%
filter(name %in% creator_out_edges$to)
# Step 4: Get all outgoing edges from songs
creator_songs_out_edges <- mc1_edges_clean %>%
filter(from %in% creator_music$name, `Edge Colour` == "Influenced By")
# Step 5: First join to get creator names (from)
creators <- creator_out_edges %>%
left_join(mc1_nodes_clean, by = c("from" = "name")) %>%
select(from, to, node_name, `Node Type`) %>%
rename(creator_from = from, creator_name = node_name, creator_node_type = `Node Type`)
# Step 6: Second join to get song names (to)
creator_and_songs <- creators %>%
left_join(mc1_nodes_clean, by = c("to" = "name")) %>%
select(creator_from, creator_name, creator_node_type, to, node_name, release_date, genre, notable) %>%
rename(song_name = node_name, song_genre = genre, song_to = to) %>%
distinct()
# Step 7: Third join to get song's influenced genre (to)
creator_and_songs_and_influenced_by <- creator_and_songs %>%
left_join(creator_songs_out_edges %>% select(from, to), by = c("song_to" = "from"), relationship = "many-to-many") %>%
left_join(mc1_nodes_clean %>% select(name, genre), by = c("to" = "name")) %>%
rename(influenced_by_genre = genre, influenced_by = to) %>%
distinct()
# Step 8: Fourth join to get influenced song's creator
creator_and_songs_and_influenced_by_creator <- creator_and_songs_and_influenced_by %>%
left_join(creator_out_edges %>% select(from, to), by = c("influenced_by" = "to"), relationship = "many-to-many") %>%
rename(influenced_by_creator = from)Show Code
# Data Preparation
# Step 1: Get the node of the sailor
sailor_node <- creator_and_songs_and_influenced_by_creator %>%
filter(creator_name == "Sailor Shift") %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the creator produced
sailor_songs <- creator_and_songs_and_influenced_by_creator %>%
filter(creator_from == sailor_node,
creator_from != influenced_by) %>%
pull(song_to)
# Step 3: Get the songs they have influenced by
sailor_songs_influenced <- creator_and_songs_and_influenced_by_creator %>%
filter(creator_from == sailor_node,
creator_from != influenced_by) %>%
pull(influenced_by)
# Step 5: Get the creators of the influenced by songs
sailor_songs_influenced_creators <- creator_and_songs_and_influenced_by_creator %>%
filter(creator_from == sailor_node,
creator_from != influenced_by) %>%
pull(influenced_by_creator)
# Step 5: Combine all relevant node names
all_node_names <- unique(c(
sailor_node,
sailor_songs,
sailor_songs_influenced,
sailor_songs_influenced_creators
))
# Step 6: Filter graph to relevant nodes only
sub_graph <- graph %>%
filter(name %in% all_node_names)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name %in% c("Sailor Shift", "Wei Zhao"), 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == "Sailor Shift", "Sailor Shift",
ifelse(node_name == "Wei Zhao", "Wei Zhao", NA))
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)
Who has Sailor Shift been most influenced by over time?
- The table below shows all the Person and Musical Group that have influenced Sailor Shift
- Through the graph, most of the other Person and Musical Group have only produced a single music that has influenced one of her music.
- However, Wei Zhao stands out because they have influenced Sailor Shift more than once.
- Wei Zhao is the producer of Susurros de Passion that has influenced the her album Salty Dreams. Wei Zhao is also the composer of Silent Steps in the Forest’s Embrance that has influenced her song Moon Over the Tide.
- In conclusion, Ivy Echos and Wei Zhao have been the most influential on Sailor Shift’s music career.
Show Code
# Extract node data
node_data <- as_tibble(sub_graph)
# View all Person and Musical Group that has influenced Sailor Shift
node_data %>%
filter(name != "Sailor Shift", `Node Type` %in% c("Person", "MusicalGroup")) %>%
select(`Node Type`, node_name) %>%
kable() %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "200px")| Node Type | node_name |
|---|---|
| MusicalGroup | Phantom Roots |
| MusicalGroup | Ursus |
| Person | Amico Luciani |
| Person | Amy Powell |
| Person | Belinda Knappe |
| Person | Brooke Olson |
| Person | Caitlin Miller |
| Person | Cipriano Peranda |
| Person | Daniel Mccormick |
| Person | David Reese |
| Person | Debra Graham |
| Person | Dylan Schwartz |
| Person | Edward Evans |
| Person | Elmo Calbo |
| Person | Fang Ding |
| Person | Gang Shao |
| Person | Guiying Ren |
| Person | Herbert Mcfarland |
| Person | Igor Dyś |
| Person | James Henderson |
| Person | James Medina |
| Person | Jason Aguirre |
| Person | Jeremiah Love |
| Person | Jing Kang |
| Person | Joanna Avery |
| Person | Joel Long |
| Person | John Graves |
| Person | Joseph Ponce |
| Person | Joshua Taylor |
| Person | Juan Shi |
| Person | Juan Zhou |
| Person | Judy Yang |
| Person | Jun Qiao |
| Person | Jun Zhou |
| Person | Kaori Ito |
| Person | Kimberly Estrada |
| Person | Lei Fu |
| Person | Lei Jin |
| Person | Lei Shi |
| Person | Linda Burns |
| Person | Lori Massey |
| Person | Matthew Best |
| Person | Matthew Lane |
| Person | Michael Nixon |
| Person | Min Cao |
| Person | Min Long |
| Person | Ming Huang |
| Person | Ming Long |
| Person | Ming Qiao |
| Person | Ming Ren |
| Person | Ming Zhou |
| Person | Miss Jennifer Williams |
| Person | Molly Gonzalez |
| Person | Na Ye |
| Person | Naoko Sato |
| Person | Nathan Jones |
| Person | Ping Jin |
| Person | Ping Liao |
| Person | Qiang Liu |
| Person | Qiang Yuan |
| Person | Qiang Zhou |
| Person | Rachel Montes |
| Person | Rebecca Wise |
| Person | Robert Woods |
| Person | Ryan Dunlap |
| Person | Sailor Shift |
| Person | Samantha Bullock |
| Person | Sandra Burke |
| Person | Sean Jones |
| Person | Shannon Harvey |
| Person | Shawn Johnson |
| Person | Sheryl Roman |
| Person | Simone Säuberlich |
| Person | Tao Gao |
| Person | Tao Hu |
| Person | Tao Wen |
| Person | Trevor Bass |
| Person | Urszula Stochmal |
| Person | Wei Liang |
| Person | Wei Zhao |
| Person | William Robinson |
| Person | Xia Yuan |
| Person | Xiulan Fang |
| Person | Xiuying Du |
| Person | Yan Dai |
| Person | Yan Li |
| Person | Yan Tang |
| Person | Yang Peng |
| Person | Yang Wan |
| Person | Yang Zhao |
| Person | Yoko Hashimoto |
| Person | Yong Dong |
| Person | Yong Lu |
| Person | Zachary Francis |
4.3 Question 1b) Who has she collaborated with and directly or indirectly influenced?
The analysis begins with the sailor_music_all dataset from Section 4.1, filtering to retain only music with more than two inward edges. This step eliminates works without collaborators or external influences. Two Song/Albums (“The Current & The Chord” and “Salty Dreams”) have to be manually removed since their inward edges are from Sailor herself and therefore not needed. Next, all inward neighbours (source nodes) of Sailor’s music are identified, representing both influenced works (Songs/Albums) and collaborators (Persons/Musical Groups). After filtering to keep only Songs and Albums, their inward neighbours are examined. This reveals: (1) Persons/Musical Groups who have been influenced by Sailor’s music (Persons/Musical Groups), and (2) secondary influenced works (Songs/Albums) that were impacted by the same sources that were influenced by Sailor’s compositions.
Show Code
# Data Preparation
# Step 1: Get all creator names
global_creators <- mc1_nodes_clean %>%
filter(`Node Type` %in% c("Person", "MusicalGroup"))
# Step 2: Get all outgoing edges from these creators
creator_out_edges <- mc1_edges_clean %>%
filter(from %in% global_creators$name, `Edge Colour` == "Creator Of")
# Step 3: Get all songs made by creators
creator_music <- mc1_nodes_clean %>%
filter(name %in% creator_out_edges$to)
# Step 4: Get all incoming edges from songs (music and collaborators)
creator_songs_in_edges <- mc1_edges_clean %>%
filter(to %in% creator_music$name)
# Step 5: First join to get creator names (from)
creators <- creator_out_edges %>%
left_join(mc1_nodes_clean, by = c("from" = "name")) %>%
select(from, to, node_name, `Node Type`) %>%
rename(creator_name = node_name, creator_node_type = `Node Type`)
# Step 6: Second join to get song names (to)
creator_and_songs <- creators %>%
left_join(mc1_nodes_clean, by = c("to" = "name")) %>%
select(from, creator_name, creator_node_type, to, node_name, release_date, genre, notable) %>%
rename(creator_from = from, song_name = node_name, creator_release_date = release_date, song_genre = genre, song_to = to) %>%
distinct()
# Step 7: Third join to get influenced songs / collaborators
creator_and_songs_and_influences <- creator_and_songs %>%
left_join(creator_songs_in_edges %>% select(from, to, `Edge Colour`), by = c("song_to" = "to"), relationship = "many-to-many") %>%
left_join(mc1_nodes_clean %>% select(name, genre, node_name, release_date), by = c("from" = "name")) %>%
rename(influence_genre = genre, infuence_music_collaborate = from, infuence_music_collaborate_name = node_name, influence_release_date = release_date) %>%
distinct()
# Step 8: Fourth join to get influenced song's creator
creator_and_songs_and_influences_and_creators <- creator_and_songs_and_influences %>%
left_join(creator_out_edges %>% select(from, to), by = c("infuence_music_collaborate" = "to"), relationship = "many-to-many") %>%
rename(influence_creator = from)
# Step 9: Fifth join to get influenced song's creator name
creator_and_songs_and_influences_and_creators <- creator_and_songs_and_influences_and_creators %>%
left_join(mc1_nodes_clean %>% select(name, node_name), by = c("influence_creator" = "name")) %>%
rename(influence_creator_name = node_name)
# Step 10: Add release date for collaborators
creator_and_songs_and_influences_and_creators_collaborate <- creator_and_songs_and_influences_and_creators %>%
mutate(
influence_release_date = case_when(
`Edge Colour` == "Creator Of" ~ creator_release_date,
TRUE ~ influence_release_date # Keeps original value if not "Creator Of"
),
influence_creator = case_when( # A collaborator can also be considered influenced
`Edge Colour` == "Creator Of" ~ infuence_music_collaborate,
TRUE ~ influence_creator
)
)Show Code
# Data Preparation
# Step 2: Get the songs that the sailor produced
sailor_songs <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from == sailor_node,
infuence_music_collaborate != sailor_node) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
sailor_songs_collaborate_influence <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from == sailor_node,
infuence_music_collaborate != sailor_node) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
sailor_songs_influence <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from == sailor_node,
infuence_music_collaborate != sailor_node,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
sailor_songs_influence_creators <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from == sailor_node,
influence_creator != sailor_node,
!is.na(influence_creator),
infuence_music_collaborate %in% sailor_songs_influence) %>%
pull(influence_creator)
all_nodes <- unique(c(sailor_node,
sailor_songs,
sailor_songs_collaborate_influence,
sailor_songs_influence_creators))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == "Sailor Shift", 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == "Sailor Shift", "Sailor Shift", NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)
Who has she collaborated with and directly or indirectly influenced?
- The graph and table shows everyone that she has collaborated with.
- Sailor Shift has collaborated with 48 different artists and information on them can be found in the table below.
- However, Sailor Shift has not directly or indirectly influenced anyone, since none of her music has influenced others.
- For example, no Songs/Albums has referenced her Songs or Albums.
Show Code
collaboration_count <- mc1_nodes_clean %>%
filter(name %in% all_nodes,
`Node Type` %in% c("Person", "MusicalGroup"),
name != sailor_node) %>%
distinct(name) %>%
nrow()
# Print the formatted message
cat(paste0("Sailor Shift has collaborated with ", collaboration_count,
" different Persons and Musical Groups\n"))Sailor Shift has collaborated with 48 different Persons and Musical GroupsShow Code
mc1_nodes_clean %>%
filter(name %in% all_nodes,
`Node Type` %in% c("Person", "MusicalGroup"),
name != sailor_node) %>%
arrange(release_date) %>%
select(`Node Type`, node_name) %>%
kable() %>%
scroll_box(height = "200px")| Node Type | node_name |
|---|---|
| MusicalGroup | Crimson Carriage |
| MusicalGroup | Ivy Echos |
| MusicalGroup | Selkie's Hollow |
| MusicalGroup | Siren's Call |
| MusicalGroup | The Brine Choir |
| MusicalGroup | The Wave Riders |
| MusicalGroup | Tidal Reverie |
| MusicalGroup | Violet Engines |
| Person | Aiden Harper |
| Person | Arlo Sterling |
| Person | Astrid Nørgaard |
| Person | Beatrice Albright |
| Person | Cassian Rae |
| Person | Coralia Bellweather |
| Person | Daniel O'Connell |
| Person | Elara May |
| Person | Ethan Clarke |
| Person | Ewan MacCrae |
| Person | Finn McGraw |
| Person | Finn Morgan |
| Person | Fiona Mercer |
| Person | Freya Lindholm |
| Person | Iris Moon |
| Person | Jade Thompson |
| Person | Jonah Calloway |
| Person | Kai Reynolds |
| Person | Kara Lee |
| Person | Levi Holloway |
| Person | Lia Grant |
| Person | Liam O'Sullivan |
| Person | Lila "Lilly" Hartman |
| Person | Lila Rivers |
| Person | Lucas Bennett |
| Person | Lyra Blaze |
| Person | Marin Thorne |
| Person | Maya Jensen |
| Person | Maya Torres |
| Person | Mia Waters |
| Person | Michael Harris |
| Person | Olivia Carter |
| Person | Orion Cruz |
| Person | Rusty Riggins |
| Person | Skylar Brooks |
| Person | Sophie Bennett |
| Person | Sophie Ramirez |
| Person | William Tidewell |
| Person | Zachary Cole |
| Person | Zane Cruz |
4.4 Question 1c) How has she influenced collaborators of the broader Oceanus Folk community?
This question is tackled by first identifying all Songs and Albums belonging to the Oceanus Folk Genre and retriving their associated artists (Persons/Musical Groups). Then Sailor Shift’s is identified and her degree of separation is calculated to examine her impact on the broader Oceanus Folk community.
Show Code
genre_creators = creator_and_songs_and_influences_and_creators_collaborate %>%
filter(song_genre == "Oceanus Folk") %>%
pull(creator_from)
genre_music = creator_and_songs_and_influences_and_creators_collaborate %>%
filter(song_genre == "Oceanus Folk") %>%
pull(song_to)
genre_all_nodes <- unique(c(genre_creators,
genre_music))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% genre_all_nodes)
chosen_degree = 13
# Data Preparation
# Convert to igraph object
sub_igraph <- as.igraph(sub_graph)
# Find Sailor Shift's vertex ID
artist_id <- which(V(sub_igraph)$name == sailor_node)
# Calculate distances from Sailor Shift
distances <- distances(sub_igraph, v = artist_id, mode = "all")
# Convert to tidy format, calculate distances and handle infinite values
distance_df <- tibble(
name = V(sub_igraph)$name,
degree = as.numeric(distances[1, ])
) %>%
mutate(degree = ifelse(is.infinite(degree), NA, degree))
filtered_nodes <- distance_df %>%
filter(degree <= chosen_degree) %>%
pull(name)
filtered_nodes <- unique(c(filtered_nodes,
sailor_node))
# Create subgraph
filtered_graph <- sub_graph %>%
filter(name %in% filtered_nodes) %>%
activate(nodes) %>%
left_join(distance_df, by = "name")
# Visualisation
g <- filtered_graph %>%
ggraph(layout = "kk") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = degree,
shape = `Node Type`,
size = ifelse(node_name %in% c("Sailor Shift"), 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Degree: %s", node_name, genre, notable, release_date, degree
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s<br/>Degree: %s", node_name, genre, notable, release_date, single, degree
),
TRUE ~ sprintf("%s<br/>Degree: %s", node_name, degree)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == "Sailor Shift", "Sailor Shift", NA)
),
fontface = "bold",
size = 3,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity() +
scale_color_gradientn(
name = "Degree",
colours = c("#2E3192", "#FFA757"),
values = scales::rescale(c(0, 13)),
na.value = "grey50",
limits = c(0, 13),
breaks = 0:13
)
girafe(ggobj = g, width_svg = 9, height_svg = 8)
How has she influenced collaborators of the broader Oceanus Folk community?
- This graph is displays a network overview of all People/Musical Groups who have produced Oceanus Folk Songs/Albums.
- While Sailor Shift is connected to a portion of the Oceanus Folk community, most artists in this genre remain outside her influence network - either as distant connections (3rd to 13th degree) or completely unconnected.
- In conclusion, Sailor Shift has a moderate influence on the broader Oceanus Folk community since her impact is discernible but not widespread.
Other Insights
- It seems that the Oceanus Folk community places a strong emphasis on collaboration
- Rather than simply drawing influence from each other’s work, they prefer collaborating directly
- Evidenced by the sporadic ‘Influenced By’ connections in the network graph
5 VAST 2025 MC1 Question 2
Develop visualizations that illustrate how the influence of Oceanus Folk has spread through the musical world.
4 Exploratory Data Analysis (EDA) - Sailor’s Network
- In total, Sailor Shift released 38 Songs and Albums from 2024 to 2040
- Details on the Songs and Albums can be found in the table below
- Sailor Shift released 4 Songs in 2028
- Among those, only 1 is a Single
- Therefore, the viral Song that spark her breakthrough is High Tide Heartbeat
- Among her Songs and Albums, 36 belong to the Oceanus Folk genre, while there is 1 Americana and 1 Synthwave Album each.
Show Code
# Step 0: Get name of 'Sailor Shift'
sailor_vertex_name <- mc1_nodes_clean %>%
filter(is_sailor == TRUE) %>%
pull(name)
# Step 1: Find outgoing edges from Sailor Shift
sailor_out_edges <- mc1_edges_clean %>%
filter(from == sailor_vertex_name)
# Step 2: Identify neighbour node names
sailor_out_node_names <- sailor_out_edges$to
# Step 4: Identify songs/albums
sailor_music_all <- mc1_nodes_clean %>%
filter(name %in% sailor_out_node_names, `Node Type` %in% c("Song", "Album")) %>%
pull(name)
mc1_nodes_clean %>%
filter(name %in% sailor_music_all) %>%
arrange(release_date) %>%
select(`Node Type`, node_name, release_date, genre, notable, single, notoriety_date) %>%
kable() %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "300px")| Node Type | node_name | release_date | genre | notable | single | notoriety_date |
|---|---|---|---|---|---|---|
| Album | The Kelp Forest Canticles | 2024 | Oceanus Folk | TRUE | NA | NA |
| Album | Luminescent Tides | 2025 | Oceanus Folk | TRUE | NA | NA |
| Album | Shoreline Sonnets | 2026 | Oceanus Folk | TRUE | NA | NA |
| Album | Tidal Pop Waves | 2028 | Oceanus Folk | TRUE | NA | NA |
| Song | Chord of the Deep | 2028 | Oceanus Folk | FALSE | FALSE | NA |
| Song | Electric Eel Love | 2028 | Oceanus Folk | TRUE | FALSE | NA |
| Song | High Tide Heartbeat | 2028 | Oceanus Folk | FALSE | TRUE | NA |
| Song | Sun-Drenched Daydream | 2028 | Oceanus Folk | FALSE | FALSE | NA |
| Album | Tides of Echos | 2029 | Oceanus Folk | TRUE | NA | NA |
| Album | Salty Dreams | 2030 | Oceanus Folk | TRUE | NA | NA |
| Song | Driftwood Lullaby | 2030 | Oceanus Folk | FALSE | FALSE | NA |
| Song | Heart of the Habitat | 2030 | Oceanus Folk | FALSE | TRUE | NA |
| Song | Reef Rhythm | 2030 | Oceanus Folk | FALSE | FALSE | NA |
| Song | Seashell Serenade | 2030 | Oceanus Folk | TRUE | TRUE | 2030 |
| Album | Hidden Depths | 2031 | Oceanus Folk | TRUE | NA | NA |
| Album | Neon Heartbeat | 2031 | Synthwave | FALSE | NA | NA |
| Album | Submerged Sonatas | 2031 | Oceanus Folk | TRUE | NA | NA |
| Album | Tidesworn Ballads | 2031 | Oceanus Folk | TRUE | NA | NA |
| Album | The Current & The Chord | 2032 | Oceanus Folk | TRUE | NA | NA |
| Song | Saltwater Hymn | 2032 | Oceanus Folk | FALSE | FALSE | NA |
| Album | Ballads for the End of Time | 2033 | Oceanus Folk | TRUE | NA | NA |
| Album | Melancholy Circuitry | 2033 | Americana | TRUE | NA | NA |
| Album | Coral Beats | 2034 | Oceanus Folk | TRUE | NA | NA |
| Album | Drifting Between the Stars and the Sea | 2034 | Oceanus Folk | TRUE | NA | NA |
| Song | Barnacle Heart | 2034 | Oceanus Folk | FALSE | FALSE | NA |
| Song | Into the Current | 2034 | Oceanus Folk | FALSE | TRUE | NA |
| Song | Moon Over the Tide | 2034 | Oceanus Folk | TRUE | FALSE | NA |
| Album | Artificial Sunsets | 2035 | Oceanus Folk | TRUE | NA | NA |
| Album | Tides & Ballads | 2036 | Oceanus Folk | TRUE | NA | NA |
| Song | Fog & Fiddle | 2036 | Oceanus Folk | TRUE | FALSE | NA |
| Song | The Fisherman's Prayer | 2036 | Oceanus Folk | FALSE | TRUE | NA |
| Album | Ballads for the Low Tide | 2037 | Oceanus Folk | TRUE | NA | NA |
| Album | Electric Reverie | 2038 | Oceanus Folk | TRUE | NA | NA |
| Album | Oceanbound | 2038 | Oceanus Folk | TRUE | NA | NA |
| Song | Stormsong | 2038 | Oceanus Folk | TRUE | TRUE | NA |
| Album | Echoes of the Deep | 2040 | Oceanus Folk | TRUE | NA | NA |
| Song | Salt in My Veins | 2040 | Oceanus Folk | FALSE | FALSE | NA |
| Song | The Last Mariner | 2040 | Oceanus Folk | FALSE | FALSE | NA |
Show Code
# Prepare data
sailor_release_data <- mc1_nodes_clean %>%
filter(name %in% sailor_music_all) %>%
count(release_date, genre)
# Plot
ggplot(sailor_release_data, aes(x = release_date, y = n, fill = genre)) +
geom_col() +
geom_vline(xintercept = 2028, linetype = "dashed", color = "red") +
annotate("text",
x = 2028,
y = max(sailor_release_data$n) + 0.5,
label = "Viral Breakthrough",
color = "red",
size = 3.5,
angle = 0, # <- horizontal
vjust = -0.5, # <- moves it slightly above
hjust = 0.5 # <- centers it horizontally
) +
scale_fill_brewer(palette = "Pastel1") +
labs(
title = "Sailor Shift's Music Releases (2024–2040)",
x = "Year",
y = "Number of Songs/Albums",
fill = "Genre"
) +
theme_minimal()
5.1 Question 2a) Was this influence intermittent or did it have a gradual rise?
We will explore these three areas to understand the influence of Oceanus Folk over time:
Yearly number of Oceanus Folk Music releases
Yearly number of works influenced by Oceanus Folk Music
Yearly number of Oceanus Folk Artists, Influenced Artists and Collaborators
5.1.1 Yearly number of Oceanus Folk Music releases
The number of Oceanus Folk Music (Songs/Albums) releases that were released each year are obtained using the codes below:
Show Code
# Data Preparation
# Step 1: Get all node names in Oceanus Folk genre
oceanus_nodes <- mc1_nodes_clean %>%
filter(genre == "Oceanus Folk") %>%
pull(name)
# Step 2: Count number of oceanus folk nodes by release date
oceanus_nodes_by_date <- mc1_nodes_clean %>%
filter(name %in% unique(oceanus_nodes)) %>%
count(release_date, name = "oceanus_nodes_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(oceanus_nodes_count))
# Visualisation
plot_ly(
data = oceanus_nodes_by_date,
x = ~release_date,
y = ~oceanus_nodes_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", oceanus_nodes_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Oceanus Folk Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
),
annotations = list(
list(
x = 2024,
y = 280,
text = "<b>2024: Sailor Shift's Debut</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -40,
font = list(color="#2E3192", size=12)
),
list(
x = 2028,
y = 320,
text = "<b>2028: Sailor Shift's Breakthrough</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -40,
font = list(color="#2E3192", size=12)
)
),
shapes = list(
list(
type = "line",
x0 = 2024, x1 = 2024,
y0 = 0, y1 = 280,
line = list(dash="dash", color="grey")
),
list(
type = "line",
x0 = 2028, x1 = 2028,
y0 = 0, y1 = 320,
line = list(dash="dash", color="grey")
)
)
)Insights
The chart illustrates the rise of Oceanus Folk music from its origins in 1992 to 2040. The blue bars represent the number of Oceanus Folk songs or albums released each year, highlighting notable spikes especially in the mid-2020s.
The red line shows the cumulative total of Oceanus Folk releases over time, which demonstrates a steady and sustained growth in Oceanus Folk music. This growth before plateauing in 2040, indicating that the genre has matured.
Two key milestones in Sailor Shift’s career - her solo debut in 2024 and breakthrough in 2028 were also mapped in the chart. The significant increases in Oceanus Folk music releases occurred in 2023 and 2026, which were the years immediately before and after her key milestones. This suggests that Sailor Shift’s emergence coincided with a rising wave of Oceanus Folk music, and that her success helped to fuel the genre’s growth in the subsequent years.
5.1.2 Influence based on number of works that were influenced by Oceanus Folk music
To measure how Oceanus Folk influenced the broader music landscape, we tracked how often songs and albums from other genres were influenced by Oceanus Folk works. These influence relationships were drawn from edge types consisting InStyleOf, CoverOf, InterpolatesFrom, LyricalReferenceTo, and DirectlySamples.
We then focused on edges where an Oceanus Folk song or album is the target (to), and the source (from) is the influenced work. The release date of each influenced work and number of such works for each year were extracted. To reveal long-term trends, cumulative total of influenced works are calculated.
The above approach is reflected in the codes below:
Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_yearly <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(song_to %in% unique(oceanus_nodes),
`Edge Colour` == "Influenced By",
infuence_music_collaborate != song_to) %>%
distinct(infuence_music_collaborate, influence_release_date) %>%
count(influence_release_date, name = "num_influenced_nodes") %>%
complete(influence_release_date = 1975:2040, fill = list(num_influenced_nodes = 0)) %>%
arrange(influence_release_date) %>% # Ensure dates are in chronological order
filter(cumsum(num_influenced_nodes) > 0) %>%
mutate(cumulative_influenced = cumsum(num_influenced_nodes))
# Visualisation
plot_ly(
data = influence_yearly,
x = ~influence_release_date,
y = ~num_influenced_nodes,
type = "bar",
name = "Number of Influenced Songs/Albums",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0("Year: ", influence_release_date, "<br>Influenced: ", num_influenced_nodes)
) %>%
add_trace(
y = ~cumulative_influenced,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Influenced",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0("Year: ", influence_release_date, "<br>Cumulative: ", cumulative_influenced)
) %>%
layout(
title = "Yearly Oceanus Folk Music Influence on Songs/Albums",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE,
range = c(1990, 2040)
),
yaxis = list(
title = "Count",
automargin = TRUE,
range = c(0, 300)
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
),
annotations = list(
list(
x = 2024,
y = 250,
text = "<b>2024: Sailor Shift's Debut</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -40,
font = list(color = "#2E3192", size = 12)
),
list(
x = 2028,
y = 280,
text = "<b>2028: Sailor Shift's Breakthrough</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -40,
font = list(color = "#2E3192", size = 12)
)
),
shapes = list(
list(
type = "line",
x0 = 2024, x1 = 2024,
y0 = 0, y1 = 280,
line = list(dash = "dash", color = "grey")
),
list(
type = "line",
x0 = 2028, x1 = 2028,
y0 = 0, y1 = 320,
line = list(dash = "dash", color = "grey")
)
)
)Insights
This chart shows the rise of Oceanus Folk music as a source of influence in the music landscape over time since it was introduced in 1992. The blue bars represent the number of influence works each year and the red line shows the cumulative total showing long-term trends.
From the 1990s through early 2000s, Oceanus Folk had very few influenced work. From 2010s onwards, Oceanus Folk music became more influential, followed by several spikes between 2010 and 2022, showing growing influence of the genre before Sailor Shift’s debut.
In 2023, there was a sharp increase in both the number of yearly influenced works and the cumulative total. The rising wave of Oceanus Folk influenced music had coincided with Sailor Shift’s rise and the influence continued to accelerate with Sailor’s breakthrough until 2029.
After 2030, the influence tapers off, suggesting the genre may have matured or plateaued.
5.1.3 Influence based on number of Oceanus Folk Artists and Influenced Artists
We examined the network of people and groups involved in Oceanus Folks music creation and influence. Our analysis begins by identifying all artists (i.e. Person and Musical Group) directly connected to Oceanus Folk music via these edges (PerformerOf, ComposerOf , ProducerOf, LyricistOf ) for Oceanus Folk songs and albums. We also added members of musical groups (i.e. collaborators) that contributed to Oceanus Folk works.
In parallel, we traced those influenced by Oceanus Folk: people and groups who created songs or albums influenced by Oceanus works music (i.e. with edges belonging to InStyleOf, InterpolatesFrom, CoverOf, LyricalReferenceTo and DirectlySamples). Similarly, members of musical groups (i.e. collaborators) that created works influenced by Oceanus Folk works were included.
Together, these artists form a comprehensive view of Oceanus Folk’s influence on the music landscape.
Show Code
# Step 1: Count number of influenced artists by release date
creators_by_date <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(song_to %in% unique(oceanus_nodes),
influence_creator != creator_from) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "people_count") %>%
arrange(first_influence_date) %>%
rename(influence_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(people_count))
# Visualisation
plot_ly(
data = creators_by_date,
x = ~influence_release_date,
y = ~people_count,
type = "bar",
name = "Number of Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", influence_release_date,
"<br>Count: ", people_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", influence_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Number of New Oceanus Folk Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
),
annotations = list(
list(
x = 2024,
y = 800,
text = "<b>2024: Sailor Shift's Debut</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -40,
font = list(color="#2E3192", size=12)
),
list(
x = 2028,
y = 1120,
text = "<b>2028: Sailor Shift's Breakthrough</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -40,
font = list(color="#2E3192", size=12)
)
),
shapes = list(
list(
type = "line",
x0 = 2024, x1 = 2024,
y0 = 0, y1 = 800,
line = list(dash="dash", color="grey")
),
list(
type = "line",
x0 = 2028, x1 = 2028,
y0 = 0, y1 = 1120,
line = list(dash="dash", color="grey")
)
)
)Insights
This chart shows the rise of Oceanus Folk music as a source of influence in the music landscape over time since it was introduced in 1992. The blue bars represent the number of influence works each year and the red line shows the cumulative total showing long-term trends.
From the 1990s through early 2000s, Oceanus Folk had very few influenced work. From 2010s onwards, Oceanus Folk music became more influential, followed by several spikes between 2010 and 2022, showing growing influence of the genre before Sailor Shift’s debut.
In 2023, there was a sharp increase in both the number of yearly influenced works and the cumulative total. The rising wave of Oceanus Folk influenced music had coincided with Sailor Shift’s rise and the influence continued to accelerate with Sailor’s breakthrough until 2029.
After 2030, the influence tapers off, suggesting the genre may have matured or plateaued.
# Step 2: Select and rename columns
df1 <- oceanus_nodes_by_date %>%
select(year = release_date, value = cumulative_count) %>%
mutate(series = "Music Releases")
df2 <- influence_yearly %>%
select(year = influence_release_date, value = cumulative_influenced) %>%
mutate(series = "Influenced Songs/Albums")
df3 <- creators_by_date %>%
select(year = influence_release_date, value = cumulative_count) %>%
mutate(series = "New Influenced Artists")
# Step 3: Combine into one tidy data frame
combined_df <- bind_rows(df1, df2, df3)
# Step 4: Plot
plot_ly(combined_df,
x = ~year,
y = ~value,
color = ~series,
colors = c("Music Releases" = "#ADD8E6",
"Influenced Songs/Albums" = "#F08080",
"New Influenced Artists" = "#C2E0C6"),
type = 'scatter',
mode = 'lines+markers',
hoverinfo = "text",
hovertext = ~paste0("Year: ", year, "<br>", series, ": ", value)
) %>%
layout(
title = list(text = "Oceanus Folk Influence Over Time (Cumulative)", x = 0.5),
xaxis = list(title = list(text = ""), dtick = 5),
yaxis = list(title = "Cumulative Count"),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = 1.15, # position legend above the plot
yanchor = "bottom"
),
margin = list(t = 160, b = 80),
# Add annotations
annotations = list(
list(
x = 2024,
y = 800,
text = "<b>2024: Sailor Shift's Debut</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE,
arrowhead = 2,
ax = -30, ay = -40,
font = list(color = "#2E3192", size = 12)
),
list(
x = 2028,
y = 1120,
text = "<b>2028: Sailor Shift's Breakthrough</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE,
arrowhead = 2,
ax = -30, ay = -40,
font = list(color = "#2E3192", size = 12)
)
),
# Add vertical dashed lines
shapes = list(
list(
type = "line",
x0 = 2024, x1 = 2024,
y0 = 0, y1 = 800,
line = list(dash = "dash", color = "grey")
),
list(
type = "line",
x0 = 2028, x1 = 2028,
y0 = 0, y1 = 1120,
line = list(dash = "dash", color = "grey")
)
)
)# Step 1: Prepare tidy data frame with yearly counts (not cumulative)
df1_counts <- oceanus_nodes_by_date %>%
select(year = release_date, value = oceanus_nodes_count) %>%
mutate(series = "Music Releases")
df2_counts <- influence_yearly %>%
select(year = influence_release_date, value = num_influenced_nodes) %>%
mutate(series = "Influenced Songs/Albums")
df3_counts <- creators_by_date %>%
select(year = influence_release_date, value = people_count) %>%
mutate(series = "New Influenced Artists")
combined_counts_df <- bind_rows(df1_counts, df2_counts, df3_counts)
# Step 2: Create faceted bar plot with horizontal layout
p <- ggplot(combined_counts_df, aes(x = year, y = value, fill = series)) +
geom_col(show.legend = FALSE) +
facet_wrap(~series, nrow = 1, scales = "fixed") + # horizontal facets
scale_fill_manual(values = c("Music Releases" = "#ADD8E6",
"Influenced Songs/Albums" = "#F08080",
"New Influenced Artists" = "#C2E0C6")) +
labs(title = "Yearly Numbers by Category",
x = NULL, y = "Yearly Count") +
theme_minimal()+
theme(legend.position = "none", panel.spacing = unit(1.5, "lines"), plot.title = element_text(hjust = 0.5)) # fully removes legend
# Step 3: Make it interactive
ggplotly(p)5.1.3.1 Genre Star Factor
Show Code
# Step 1: First get the song-level influence data (similar to your Step 10)
song_influence_lists <- creator_and_songs_and_influences_and_creators_collaborate %>%
group_by(song_to, song_name, creator_release_date, song_genre, notable) %>%
distinct () %>%
summarize(
unique_collaborate = list(unique(na.omit(infuence_music_collaborate[creator_from != influence_creator & `Edge Colour` == "Creator Of"]))),
unique_influence_creators = list(unique(na.omit(influence_creator[creator_from != influence_creator & `Edge Colour` == "Influenced By"]))),
unique_influence_music = list(unique(na.omit(infuence_music_collaborate[creator_from != influence_creator & !is.na(influence_genre)])))
)
# Step 2: Aggregate statistics by genre
genre_stats <- song_influence_lists %>%
group_by(song_genre) %>%
summarize(
total_songs = n_distinct(song_to),
notable_hits = sum(notable == TRUE, na.rm = TRUE),
collaboration = length(unique(unlist(unique_collaborate))),
influence_creators = length(unique(unlist(unique_influence_creators))),
collaboration_influence_creator = length(unique(c(unlist(unique_influence_creators),unlist( unique_collaborate)))),
influence_music = length(unique(unlist(unique_influence_music)))
)
# Step 12: Create Scoring Rubric
genre_rankings <- genre_stats %>%
mutate(
# Normalize each metric (0-1 scale)
songs_score = (total_songs - min(total_songs)) / (max(total_songs) - min(total_songs)),
notable_score = (notable_hits - min(notable_hits)) / (max(notable_hits) - min(notable_hits)),
artists_score = (collaboration_influence_creator - min(collaboration_influence_creator)) / (max(collaboration_influence_creator) - min(collaboration_influence_creator)),
music_score = (influence_music - min(influence_music)) / (max(influence_music) - min(influence_music)),
# Calculate composite score (equal weighting)
composite_score = songs_score + notable_score + artists_score + music_score
) %>%
arrange(desc(composite_score)) %>%
select(song_genre, total_songs, notable_hits, collaboration_influence_creator, influence_music, composite_score)
# Step 13: Final Ranked Table
genre_rankings %>%
mutate(
Rank = row_number(),
`Star Factor` = round(composite_score, 2)
) %>%
select(Rank, song_genre, total_songs, notable_hits, collaboration_influence_creator,
influence_music, `Star Factor`) %>%
rename(
`Genre` = song_genre,
`Total Music` = total_songs,
`Notable Hits` = notable_hits,
`Artist Influ & Colab` = collaboration_influence_creator,
`Music Influenced` = influence_music
) %>%
kable(caption = "Genre Ranked by Star Factor") %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "300px")| Rank | Genre | Total Music | Notable Hits | Artist Influ & Colab | Music Influenced | Star Factor |
|---|---|---|---|---|---|---|
| 1 | Dream Pop | 742 | 709 | 3254 | 589 | 3.91 |
| 2 | Indie Folk | 450 | 432 | 2645 | 603 | 2.95 |
| 3 | Doom Metal | 348 | 335 | 2614 | 646 | 2.73 |
| 4 | Synthwave | 382 | 364 | 2266 | 496 | 2.48 |
| 5 | Oceanus Folk | 305 | 244 | 1168 | 244 | 1.48 |
| 6 | Psychedelic Rock | 172 | 168 | 1518 | 277 | 1.35 |
| 7 | Indie Rock | 208 | 196 | 1211 | 248 | 1.30 |
| 8 | Alternative Rock | 258 | 251 | 793 | 226 | 1.28 |
| 9 | Southern Gothic Rock | 242 | 231 | 645 | 285 | 1.28 |
| 10 | Americana | 184 | 173 | 1043 | 165 | 1.05 |
| 11 | Indie Pop | 134 | 122 | 414 | 199 | 0.77 |
| 12 | Desert Rock | 125 | 120 | 826 | 107 | 0.74 |
| 13 | Jazz Surf Rock | 127 | 123 | 641 | 120 | 0.71 |
| 14 | Space Rock | 121 | 113 | 696 | 81 | 0.64 |
| 15 | Lo-Fi Electronica | 136 | 127 | 218 | 127 | 0.61 |
| 16 | Darkwave | 104 | 97 | 545 | 102 | 0.58 |
| 17 | Blues Rock | 109 | 103 | 393 | 122 | 0.58 |
| 18 | Post-Apocalyptic Folk | 72 | 66 | 502 | 88 | 0.46 |
| 19 | Symphonic Metal | 64 | 56 | 491 | 88 | 0.43 |
| 20 | Emo/Pop Punk | 77 | 72 | 182 | 95 | 0.39 |
| 21 | Avant-Garde Folk | 70 | 64 | 185 | 97 | 0.37 |
| 22 | Speed Metal | 84 | 76 | 160 | 73 | 0.36 |
| 23 | Synthpop | 46 | 41 | 310 | 52 | 0.28 |
| 24 | Sea Shanties | 21 | 4 | 4 | 0 | 0.01 |
| 25 | Acoustic Folk | 18 | 7 | 3 | 0 | 0.01 |
| 26 | Celtic Folk | 12 | 3 | 5 | 1 | 0.00 |
(didnt copy over combined plot)
5.1.4 Bayesian Surprise
We have analysed the Oceanus Folks music influence trends over time using line and bar charts. Besides visual plots, we can quantify if the influence was intermittent or gradual using the statistical tool - Bayesian Surprise.
Bayesian Surprise is a concept in information theory, which is used to identify moments of unexpected change in sequential data. Based our research, it is suitable for analysing trends like the spread of musical influence and temporal pattern detection.
To compute Bayesian Surprise, we treat each year as a new observation and compare the current year’s count to the prior expectation which is modelled using a Poisson probability distribution which is suitable for our count data across years.
These are the steps in generating the Surprise Score:
Obtain the yearly time series data from the previous 3 analysis.
Model prior belief based on previous year(s)
Compute posterior with the new data
Calculate Bayesian Surprise as the KL divergence (Kullback–Leibler divergence) between the prior and posterior
The Surprise Computation Function is defined using the following codes:
Show Code
library(zoo)
# Define general function to compute Bayesian Surprise
compute_bayesian_surprise <- function(data, year_col, count_col, window = 5) {
data <- data %>%
rename(year = {{year_col}}, count = {{count_col}}) %>%
complete(year = min(year):max(year), fill = list(count = 0)) %>%
arrange(year)
# Calculate moving average (prior belief)
data <- data %>%
mutate(prior_mean = rollmean(count, k = window, align = "right", fill = NA))
# Compute KL Divergence for Poisson distributions
data <- data %>%
mutate(
surprise = ifelse(
!is.na(prior_mean) & prior_mean > 0 & count > 0,
count * log(count / prior_mean) - (count - prior_mean),
NA
)
)
return(data)
}Bayesian Surprise is computed using KL Divergence between each year’s observed value and a rolling average of the previous five years, treating yearly counts as Poisson-distributed events using the following:
Show Code
# 1. Surprise for Oceanus Folk releases
surprise_releases <- compute_bayesian_surprise(
oceanus_nodes_by_date,
release_date,
oceanus_nodes_count,
window = 5
)
# 2. Surprise for influenced works
surprise_influence <- compute_bayesian_surprise(
influence_yearly,
influence_release_date,
num_influenced_nodes,
window = 5
)
# 3. Surprise for artists and contributors
surprise_contributors <- compute_bayesian_surprise(
creators_by_date,
influence_release_date,
people_count,
window = 5
)Bayesian Surprise Across Oceanus Folk Music Releases, Influenced Works, and Artists
Show Code
plot_data <- bind_rows(
surprise_releases %>% select(year, surprise) %>% mutate(type = "Music Releases"),
surprise_influence %>% select(year, surprise) %>% mutate(type = "Influenced Works"),
surprise_contributors %>% select(year, surprise) %>% mutate(type = "Artists")
) %>%
filter(!is.na(surprise), year >= 1990)
# Plot using Plotly
plot_ly(data = plot_data, x = ~year, y = ~surprise, color = ~type, colors = "Set1",
type = 'scatter', mode = 'lines+markers',
hoverinfo = "text",
hovertext = ~paste0("Year: ", year,
"<br>Category: ", type,
"<br>Surprise: ", round(surprise, 2))) %>%
layout(
title = "Bayesian Surprise Across Oceanus Folk Music Releases, Influenced Works, and Artists",
xaxis = list(title = "Year", dtick = 5, range = c(1990, max(plot_data$year))),
yaxis = list(title = "Surprise Score (KL Divergence)"),
legend = list(orientation = "h", x = 0.5, xanchor = "center", y = -0.2),
margin = list(t = 60, b = 80)
)unique(plot_data$type)[1] "Music Releases" "Influenced Works" "Artists" plot_data <- plot_data %>%
mutate(type = case_when(
type == "Music Releases" ~ "Music Releases",
type == "Influenced Works" ~ "Influenced Songs/Albums",
type == "Artists" ~ "New Influenced Artists",
TRUE ~ type
))
plot_ly(
data = plot_data,
x = ~year,
y = ~surprise,
color = ~type,
colors = c(
"Music Releases" = "#ADD8E6",
"Influenced Songs/Albums" = "#F08080",
"New Influenced Artists" = "#C2E0C6"
),
type = 'scatter',
mode = 'lines+markers',
hoverinfo = "text",
hovertext = ~paste0(
"Year: ", year,
"<br>Category: ", type,
"<br>Surprise: ", round(surprise, 2)
)
) %>%
layout(
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = 1.1,
yanchor = "bottom",
font = list(size = 12)
),
title = list(
text = "Bayesian Surprise (Oceanus Folk Influenced Songs/Albums, Music Releases, and New Influenced Artists)",
x = 0.5,
xanchor = "center"
),
xaxis = list(title = "Year", dtick = 5, range = c(1990, max(plot_data$year))),
yaxis = list(title = "Surprise Score (KL Divergence)"),
margin = list(t = 160, b = 80),
# Add annotations
annotations = list(
list(
x = 2024,
y = 100,
text = "<b>2024: Sailor Shift's Debut</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE,
arrowhead = 2,
ax = -30, ay = -40,
font = list(color = "#2E3192", size = 12)
),
list(
x = 2028,
y = 120,
text = "<b>2028: Sailor Shift's Breakthrough</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE,
arrowhead = 2,
ax = -30, ay = -40,
font = list(color = "#2E3192", size = 12)
)
),
# Add vertical dashed lines
shapes = list(
list(
type = "line",
x0 = 2024, x1 = 2024,
y0 = 0, y1 = 100,
line = list(dash = "dash", color = "grey")
),
list(
type = "line",
x0 = 2028, x1 = 2028,
y0 = 0, y1 = 120,
line = list(dash = "dash", color = "grey")
)
)
)Insights
The Bayesian Surprise analysis showed that Oceanus Folk’s influence was intermittent rather than a smooth, gradual rise. While cumulative trends in music releases, influenced works and artist numbers may suggest steady growth, Bayesian Surprise uncovers a different insight that there were indeed intermittent surges of activity.
For example, the sharp peaks in surprise scores for artists (red line) in years like 2004, 2010, 2017, and especially 2023 suggest that Oceanus Folk influence had waves of breakthroughs and not slow accumulation.
Influenced works (blue line) increased in 2017, spiked in 2023 and sustained its increase across 2030 to 2033, which shows how Sailor’s debut and breakthrough had catalysed Oceanus Folk genre influence.
Music releases (green line) generally showed lower surprise, which confirms that number of Oceanus Folks music was not a key driver to influence.
Thus, while the overall trend shows long-term growth, Bayesian Surprise confirms that Oceanus Folk’s rise was intermittent and driven by burst such as artist breakthrough. Such bursts also maintained the momentum of the influence for an interval of time.
5.2 Question 2b) What genres and top artists have been most influenced by Oceanus Folk?
5.2.1 What genres have been most influenced by Oceanus Folk?
To determine which genres have been most influenced by Oceanus Folk, all songs and albums were identified. Then, the music (Songs/Albums) that influenced them were obtained to calculate the frequency and percentage of Oceanus Folk’s influence across different musical genre. This analysis reveals the genres that show the strongest impact from Oceanus Folk’s musical style.
Show Code
genre_influence_stats <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(infuence_music_collaborate != song_to) %>%
distinct(song_to, song_genre, infuence_music_collaborate, influence_genre, `Edge Colour`) %>%
group_by(song_genre) %>%
summarize(
total_music = n_distinct(song_to),
total_influences = n_distinct(na.omit(infuence_music_collaborate[!is.na(influence_genre)])),
oceanus_influences = n_distinct(na.omit(infuence_music_collaborate[influence_genre == "Oceanus Folk"])),
other_influences = total_influences - oceanus_influences,
perc_oceanus = round(oceanus_influences / total_influences * 100, 1),
no_influences = sum(is.na(influence_genre)),
) %>%
arrange(desc(oceanus_influences))
genre_influence_stats %>%
kable(caption = "Genre Ranked by Oceanus Influence") %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "300px")| song_genre | total_music | total_influences | oceanus_influences | other_influences | perc_oceanus | no_influences |
|---|---|---|---|---|---|---|
| Oceanus Folk | 305 | 244 | 97 | 147 | 39.8 | 1058 |
| Indie Folk | 450 | 603 | 93 | 510 | 15.4 | 1938 |
| Synthwave | 382 | 496 | 16 | 480 | 3.2 | 1577 |
| Doom Metal | 348 | 646 | 14 | 632 | 2.2 | 1515 |
| Dream Pop | 742 | 591 | 14 | 577 | 2.4 | 3506 |
| Synthpop | 46 | 52 | 10 | 42 | 19.2 | 154 |
| Psychedelic Rock | 172 | 277 | 9 | 268 | 3.2 | 921 |
| Alternative Rock | 258 | 227 | 8 | 219 | 3.5 | 745 |
| Indie Rock | 208 | 248 | 8 | 240 | 3.2 | 799 |
| Desert Rock | 125 | 107 | 7 | 100 | 6.5 | 585 |
| Americana | 184 | 165 | 5 | 160 | 3.0 | 787 |
| Blues Rock | 109 | 123 | 4 | 119 | 3.3 | 313 |
| Southern Gothic Rock | 242 | 286 | 4 | 282 | 1.4 | 624 |
| Symphonic Metal | 64 | 88 | 3 | 85 | 3.4 | 277 |
| Avant-Garde Folk | 70 | 97 | 2 | 95 | 2.1 | 161 |
| Post-Apocalyptic Folk | 72 | 88 | 2 | 86 | 2.3 | 308 |
| Space Rock | 121 | 81 | 2 | 79 | 2.5 | 555 |
| Celtic Folk | 12 | 1 | 1 | 0 | 100.0 | 21 |
| Emo/Pop Punk | 77 | 96 | 1 | 95 | 1.0 | 192 |
| Indie Pop | 134 | 200 | 1 | 199 | 0.5 | 362 |
| Jazz Surf Rock | 127 | 121 | 1 | 120 | 0.8 | 491 |
| Lo-Fi Electronica | 136 | 127 | 1 | 126 | 0.8 | 390 |
| Acoustic Folk | 18 | 0 | 0 | 0 | NaN | 26 |
| Darkwave | 104 | 102 | 0 | 102 | 0.0 | 444 |
| Sea Shanties | 21 | 0 | 0 | 0 | NaN | 33 |
| Speed Metal | 84 | 74 | 0 | 74 | 0.0 | 254 |
Show Code
library(networkD3)
# Step 1: Prepare data — treat Oceanus Folk as source and include self-influence
sankey_df <- genre_influence_stats %>%
mutate(
source = "Oceanus Folk",
raw_target = ifelse(song_genre == "Oceanus Folk", "Oceanus Folk (in-genre influence)", song_genre),
value = oceanus_influences,
target = paste0(raw_target, " (", value, ")") # ← append the number
) %>%
select(source, target, value) %>%
arrange(desc(value)) %>%
head(22)
# Step 2: Create unique nodes
nodes <- data.frame(name = unique(c(sankey_df$source, sankey_df$target)))
# Step 3: Convert names to indices
links <- sankey_df %>%
mutate(
source = match(source, nodes$name) - 1,
target = match(target, nodes$name) - 1
)
# Step 4: Plot Sankey (Oceanus Folk on the left)
sankeyNetwork(
Links = links,
Nodes = nodes,
Source = "source",
Target = "target",
Value = "value",
NodeID = "name",
fontSize = 13,
nodeWidth = 30,
sinksRight = TRUE # Flow goes left (source) to right (target)
)
What genres have been most influenced by Oceanus Folk?
- The table above show the top 10 genres who was most influenced by Oceanus Folk.
- The Oceanus Folk genre has been the most influenced by itself with about 40% of all music (Songs/Albums) drawing inspiration from Oceanus Folk music.
5.2.2 Which top artists have been most influenced by Oceanus Folk?
To identify the top artists most influenced by Oceanus Folk, all artists (persons or musical groups) who either (a) created Oceanus Folk music (songs/albums) or (b) were influenced by the genre were identified. Then, all music produced by these artists, along with the musical works that influenced their creations, was counted to reveal those who were most influenced.
Show Code
creator_influenced_by_stats <- creator_and_songs_and_influenced_by_creator %>%
distinct(creator_name, creator_node_type, song_to, song_genre, influenced_by, influenced_by_genre, influenced_by_creator, notable) %>%
group_by(creator_name, creator_node_type) %>%
summarize(
total_music = n_distinct(song_to),
notable_hits = n_distinct(song_to[notable == TRUE]),
oceanus_music = n_distinct(song_to[song_genre == "Oceanus Folk"]),
oceanus_influenced_by = n_distinct(na.omit(influenced_by[influenced_by_genre == "Oceanus Folk" & creator_name != influenced_by_creator])),
total_oceanus_influence = oceanus_music + oceanus_influenced_by
) %>%
arrange(desc(total_oceanus_influence)) %>%
filter(creator_node_type == "Person", notable_hits > 10) %>%
select(-creator_node_type)
creator_influenced_by_stats %>%
head(10) %>%
rename(
`Artist` = creator_name,
`Total Music` = total_music,
`Notable Hits` = notable_hits,
`No. of Oceanus Folk Music` = oceanus_music,
`Oceanus Folk Influence` = oceanus_influenced_by,
`Oceanus Folk Music & Influence` = total_oceanus_influence
) %>%
kable(caption = "Ranking of Oceanus Folk Influence on Artists") %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "200px")| Artist | Total Music | Notable Hits | No. of Oceanus Folk Music | Oceanus Folk Influence | Oceanus Folk Music & Influence |
|---|---|---|---|---|---|
| Sailor Shift | 38 | 25 | 36 | 0 | 36 |
| Min He | 13 | 13 | 1 | 10 | 11 |
| Na Ren | 13 | 13 | 3 | 7 | 10 |
| Qiang Song | 12 | 11 | 3 | 5 | 8 |
| Min Fu | 12 | 12 | 0 | 7 | 7 |
| Ping Zeng | 11 | 11 | 1 | 6 | 7 |
| Xiuying Huang | 14 | 14 | 2 | 5 | 7 |
| Chao Qiu | 12 | 12 | 2 | 4 | 6 |
| Chao Wu | 13 | 12 | 4 | 2 | 6 |
| Yan Qin | 13 | 13 | 0 | 6 | 6 |
Show Code
# Step 1: Prepare data — treat Oceanus Folk as source and include self-influence
sankey_df <- creator_influenced_by_stats %>%
mutate(
source = "Oceanus Folk",
raw_target = creator_name,
value = total_oceanus_influence,
target = paste0(raw_target, " (", value, ")") # ← append the number
) %>%
select(source, target, value) %>%
arrange(desc(value)) %>%
head(10)
# Step 4: Nodes (no need for group column)
nodes <- data.frame(name = unique(c(sankey_df$source, sankey_df$target)))
# Step 5: Convert names to indices
links <- sankey_df %>%
mutate(
source = match(source, nodes$name) - 1,
target = match(target, nodes$name) - 1
)
# Step 6: Plot Sankey (same as before)
sankeyNetwork(
Links = links,
Nodes = nodes,
Source = "source",
Target = "target",
Value = "value",
NodeID = "name",
fontSize = 13,
nodeWidth = 30,
sinksRight = TRUE,
height = 600,
width = 1000
)
Which top artists have been most influenced by Oceanus Folk?
- The table above show the top 10 artists who was most influenced by Oceanus Folk
- These are artists who have produced Oceanus Folk music or have been influenced by it.
- Top artists are defined by having more than 10 notable hits.
- These artists are rank by the amount that Oceanus Folk has influenced them.
- The top artist is Sailor Shift who has produced 36 Oceanus Folk songs.
- The next artist is Min He, who has produced one Oceanus Folk song and has been influenced by 10 other Oceanus Folk songs, bringing the total to 11 songs.
5.3 Question 2c) On the converse, how has Oceanus Folk changed with the rise of Sailor Shift? From which genres does it draw most of its contemporary inspiration?
We will examine the diversity of musical genres that has influenced and been influenced by Oceanus Folk over time. This can be measured by Genre Entropy, which comes from information theory where higher entropy means more variety and unpredictability, while lower entropy means concentration in fewer genres, as explained by Ferwerda and Schedl (2016) in their research paper.
For our case, we will compute:
Incoming entropy = How diverse other genres were in influencing Oceanus Folk music in a given year (i.e. what genres inspired new Oceanus Folk music)
Outgoing entropy = How diverse the genres were which Oceanus Folk had influenced (i.e. what range of genres borrowed from Oceanus Folk).
By plotting both directions of entropy over time using a mirrored bar chart and mapping it against Sailor’s debut and breakthrough, we can visualise the change and impact clearly.
Show Code
# Step 1: Filter influence edges
influence_edges <- mc1_edges_clean %>%
filter(`Edge Type` %in% c("InStyleOf", "CoverOf", "InterpolatesFrom",
"LyricalReferenceTo", "DirectlySamples"))
# Step 2: Join genre and release date info
influence_genres <- influence_edges %>%
left_join(mc1_nodes_clean %>% select(name, genre), by = c("from" = "name")) %>%
rename(source_genre = genre) %>%
left_join(mc1_nodes_clean %>% select(name, genre, release_date), by = c("to" = "name")) %>%
rename(target_genre = genre, to_release = release_date) %>%
left_join(mc1_nodes_clean %>% select(name, release_date), by = c("from" = "name")) %>%
rename(from_release = release_date)
# Step 3a: Incoming entropy (genres influencing Oceanus Folk)
incoming_entropy_yearly <- influence_genres %>%
filter(target_genre == "Oceanus Folk", !is.na(source_genre), !is.na(to_release)) %>%
mutate(year = as.integer(to_release)) %>%
group_by(year, source_genre) %>%
summarise(count = n(), .groups = "drop") %>%
group_by(year) %>%
mutate(p = count / sum(count)) %>%
summarise(entropy = entropy::entropy(p, unit = "log2")) %>%
mutate(direction = "Incoming")
# Step 3b: Outgoing entropy (genres that Oceanus Folk influenced)
outgoing_entropy_yearly <- influence_genres %>%
filter(source_genre == "Oceanus Folk", !is.na(target_genre), !is.na(from_release)) %>%
mutate(year = as.integer(from_release)) %>%
group_by(year, target_genre) %>%
summarise(count = n(), .groups = "drop") %>%
group_by(year) %>%
mutate(p = count / sum(count)) %>%
summarise(entropy = entropy::entropy(p, unit = "log2")) %>%
mutate(direction = "Outgoing")
# Step 4: Combine and flip outgoing for mirrored effect
entropy_yearly <- bind_rows(
incoming_entropy_yearly,
outgoing_entropy_yearly %>% mutate(entropy = -entropy)
)
# Step 5: Plot mirrored entropy over time with hover text
entropy_plot <- ggplot(entropy_yearly, aes(
x = year, y = entropy, fill = direction,
text = paste0(
"Year: ", year,
"\nDirection: ", direction,
"\nEntropy: ", round(abs(entropy), 3), " bits"
)
)) +
geom_col(width = 0.8) +
geom_hline(yintercept = 0, color = "black") +
scale_fill_manual(
name = "Entropy Direction",
values = c("Incoming" = "lightblue", "Outgoing" = "darkblue")
) +
scale_y_continuous(
breaks = seq(-4, 4, by = 1),
labels = abs(seq(-4, 4, by = 1)),
limits = c(-4, 4)
) +
labs(
title = "Genre Entropy of Oceanus Folk Over Time",
x = "Year",
y = "Genre Entropy (bits)"
) +
theme_minimal() +
theme(legend.position = "bottom")
# Add annotations after setting `max_entropy_val`
max_entropy_val <- max(abs(entropy_yearly$entropy), na.rm = TRUE)
entropy_plot <- entropy_plot +
geom_vline(xintercept = 2024, linetype = "dashed", color = "grey50", linewidth = 0.7) +
geom_vline(xintercept = 2028, linetype = "dashed", color = "grey50", linewidth = 0.7) +
annotate("text", x = 2024.5, y = max_entropy_val + 0.4,
label = "2024: Sailor Shift's Debut",
color = "#2E3192", fontface = "bold", size = 3.5, hjust = 1) +
annotate("text", x = 2028.5, y = max_entropy_val + 0.8,
label = "2028: Sailor Shift's Breakthrough",
color = "#2E3192", fontface = "bold", size = 3.5, hjust = 1) +
annotate("segment", x = 2024.5, y = max_entropy_val + 0.4,
xend = 2024, yend = max_entropy_val - 0.2,
arrow = arrow(length = unit(0.2, "cm")), color = "grey50") +
annotate("segment", x = 2028.5, y = max_entropy_val + 0.8,
xend = 2028, yend = max_entropy_val - 0.2,
arrow = arrow(length = unit(0.2, "cm")), color = "grey50")
# Use plotly for interactivity
ggplotly(entropy_plot, tooltip = "text") %>%
layout(legend = list(orientation = "h", x = 0.5, xanchor = "center", y = -0.2))Insights
Before 2013: Limited Influence during earlier years
During the early years of Oceanus Folk, both incoming and outgoing entropy remained sparse, indicating limited cross-genre interaction. However, there are more bars for incoming entropy, showing that Oceanus Folk was more often influenced by other genres than influencing others. This suggests that during the earlier years, Oceanus Folk was still developing its identity by absorbing influence from a diverse set of genres.
2013 to 2024: Influence Growth
Between 2013 and 2024, we observe a gradual and sustained rise in both incoming and outgoing entropy.This period can be seen as the maturation phase of Oceanus Folk, where it begins to both learn from and contribute to the wider music landscape.
2024 onwards: Sailor Shift’s Rise
Incoming entropy began to decline, suggesting that Oceanus Folk was no longer absorbing influence from other genres as it solidified its musical identity.
In contrast, outgoing entropy peaked and remained elevated, reflecting that other genres increasingly drew inspiration from Oceanus Folk. This sustained high outgoing influence signals that Oceanus Folk had become a genre of reference across many genres.
5.3.2 From which genres does Oceanus Folk draw most of its contemporary inspiration?
This analysis examines the contemporary influences on Oceanus Folk by using the genre influence patterns methodology similar to Section 5.2.1.
Show Code
genre_influenced_by_stats <- creator_and_songs_and_influenced_by_creator %>%
filter(song_genre == "Oceanus Folk") %>%
distinct(song_to, influenced_by, influenced_by_genre) %>%
group_by(influenced_by_genre) %>%
summarize(
total_music = n_distinct(song_to),
influenced_by = n_distinct(na.omit(influenced_by))
) %>%
arrange(desc(influenced_by))
genre_influenced_by_stats %>%
head(10) %>%
rename(
`Genre` = influenced_by_genre,
`Total Influenced Music` = total_music,
`Influenced By Oceanus Folk` = influenced_by
) %>%
kable(caption = "Ranking of Oceanus Folk Influence on Music Genres") %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "200px")| Genre | Total Influenced Music | Influenced By Oceanus Folk |
|---|---|---|
| Oceanus Folk | 97 | 55 |
| Indie Folk | 93 | 22 |
| Synthwave | 16 | 17 |
| Dream Pop | 14 | 15 |
| Doom Metal | 14 | 13 |
| Alternative Rock | 8 | 8 |
| Psychedelic Rock | 9 | 8 |
| Desert Rock | 7 | 7 |
| Indie Rock | 8 | 7 |
| Americana | 5 | 5 |
Show Code
library(networkD3)
library(htmlwidgets)
# Step 1: Prepare data — reverse flow direction: Genre → Oceanus Folk
sankey_df <- genre_influenced_by_stats %>%
mutate(
raw_source = influenced_by_genre,
target = "Oceanus Folk",
value = influenced_by,
source = paste0(raw_source, " (", value, ")")
) %>%
select(source, target, value) %>%
arrange(desc(value)) %>%
head(22) # Top 22 genres influencing Oceanus Folk
# Step 2: Create node list
nodes <- data.frame(name = unique(c(sankey_df$source, sankey_df$target)))
# Step 3: Create link list with indices
links <- sankey_df %>%
mutate(
source = match(source, nodes$name) - 1,
target = match(target, nodes$name) - 1
)
# Step 4: Add tooltip group (Genre → Oceanus Folk)
links$group <- paste0(sankey_df$source, " → ", sankey_df$target, ": ", sankey_df$value)
# Step 5: Render Sankey
p <- sankeyNetwork(
Links = links,
Nodes = nodes,
Source = "source",
Target = "target",
Value = "value",
NodeID = "name",
fontSize = 13,
nodeWidth = 30,
sinksRight = FALSE # ← Flip layout: sources on right if needed
)
# Step 6: Add tooltips
onRender(p, '
function(el, x) {
d3.select(el)
.selectAll(".link")
.append("title")
.text(function(d) { return d.group; });
}
')
From which genres does Oceanus Folk draw most of its contemporary inspiration?
- As expected, Oceanus Folk artists primarily draw inspiration from other Oceanus Folk works, demonstrating strong genre continuity.
- Approximately a fifth of Oceanus Folk compositions appear to be original works without direct influences from existing pieces.
- Indie Folk emerges as the second most influential genre, accounting for roughly 21% of all Oceanus Folk musical references.
Reference
Figueiredo, F., Panoutsos, T., & Andrade, N. (2024, October 21). Surprising patterns in musical influence networks (Version 1) [Preprint]. arXiv. Retrieved from https://doi.org/10.48550/arXiv.2410.15996
Ferwerda, B., & Schedl, M. (2016). Investigating the relationship between diversity in music consumption behavior and cultural dimensions: A cross-country analysis (SOAP’16 workshop paper, UMAP Extended Proceedings). CEUR Workshop Proceedings, 1618. Retrieved from https://ceur-ws.org/Vol-1618/SOAP_paper1.pdf
6 VAST 2025 MC1 Question 3
Use your visualizations to develop a profile of what it means to be a rising star in the music industry.
6.1 Analysing the careers of all Artists
The analysis identifies all musical artists, including both the songs/albums they produced and their influence relationships—tracking both the musical works they have influenced and the artists they have impacted throughout their careers.
A grading rubric is added to assess artists based on four equally weighted categories:
- Number of Music Releases
- Number of Notable Music
- Number of New Artists Influenced and Collaborated With
- Number of Music Influenced
Each category’s score will be normalised using the formula:
Show Code
library(latex2exp)
plot(1, 1, type = "n", ann = FALSE, axes = FALSE)
text(1, 1,
latex2exp::TeX("$\\frac{Artist's\\ Score - min((Score))}{max((Score)) - min((Score))}$"),
cex = 2)
The Star Factor will aggregate these normalized scores (maximum: 4) to rank the artists.
Show Code
# Data Preparation
# Step 1: To highlight songs that the creator influence that is not produced by same creator
creator_influence_lists <- creator_and_songs_and_influences_and_creators_collaborate %>%
group_by(creator_name, creator_node_type, song_to, song_name, creator_release_date, song_genre, notable) %>%
distinct () %>%
summarize(
unique_collaborate = list(unique(na.omit(infuence_music_collaborate[creator_from != influence_creator & `Edge Colour` == "Creator Of"]))),
unique_influence_creators = list(unique(na.omit(influence_creator[creator_from != influence_creator & `Edge Colour` == "Influenced By"]))),
unique_influence_music = list(unique(na.omit(infuence_music_collaborate[creator_from != influence_creator & !is.na(influence_genre)])))
)
# Step 2: Aggregate unique influences per creator
creator_stats <- creator_influence_lists %>%
group_by(creator_name) %>%
summarize(
total_songs = n_distinct(song_to),
notable_hits = sum(notable == TRUE, na.rm = TRUE),
collaboration = length(unique(unlist(unique_collaborate))),
influence_creators = length(unique(unlist(unique_influence_creators))),
collaboration_influence_creator = length(unique(c(unlist(unique_influence_creators),unlist( unique_collaborate)))),
influence_music = length(unique(unlist(unique_influence_music)))
)
# Step 3: Create Scoring Rubric
creator_rankings <- creator_stats %>%
mutate(
# Normalize each metric (0-1 scale)
songs_score = (total_songs - min(total_songs)) / (max(total_songs) - min(total_songs)),
notable_score = (notable_hits - min(notable_hits)) / (max(notable_hits) - min(notable_hits)),
artists_score = (collaboration_influence_creator - min(collaboration_influence_creator)) / (max(collaboration_influence_creator) - min(collaboration_influence_creator)),
music_score = (influence_music - min(influence_music)) / (max(influence_music) - min(influence_music)),
# Calculate composite score (equal weighting)
composite_score = songs_score + notable_score + artists_score + music_score
) %>%
arrange(desc(composite_score)) %>%
select(creator_name, total_songs, notable_hits, collaboration_influence_creator, influence_music, composite_score)
# Step 4: Final Ranked Table
creator_rankings %>%
mutate(
Rank = row_number(),
`Star Factor` = round(composite_score, 2)
) %>%
select(Rank, creator_name, total_songs, notable_hits, collaboration_influence_creator,
influence_music, `Star Factor`) %>%
rename(
`Artist` = creator_name,
`Total Music` = total_songs,
`Notable Hits` = notable_hits,
`Artist Influ & Colab` = collaboration_influence_creator,
`Music Influenced` = influence_music
) %>%
kable(caption = "Artists Ranked by Star Factor") %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "300px")| Rank | Artist | Total Music | Notable Hits | Artist Influ & Colab | Music Influenced | Star Factor |
|---|---|---|---|---|---|---|
| 1 | Min Fu | 12 | 12 | 598 | 162 | 2.64 |
| 2 | Jay Walters | 37 | 35 | 51 | 50 | 2.37 |
| 3 | Jing Kang | 29 | 28 | 176 | 70 | 2.28 |
| 4 | Min Tao | 6 | 6 | 588 | 157 | 2.26 |
| 5 | Chao Tan | 5 | 5 | 592 | 155 | 2.20 |
| 6 | Ping Tian | 32 | 31 | 115 | 42 | 2.18 |
| 7 | Juan Gao | 5 | 5 | 572 | 147 | 2.11 |
| 8 | Qiang Yuan | 9 | 9 | 511 | 125 | 2.10 |
| 9 | Kimberly Snyder | 29 | 27 | 153 | 49 | 2.09 |
| 10 | Ping Meng | 24 | 23 | 175 | 83 | 2.08 |
| 11 | Yang Wan | 24 | 23 | 274 | 56 | 2.08 |
| 12 | Brett Brown | 4 | 4 | 540 | 143 | 1.98 |
| 13 | Angelika Osojca | 28 | 26 | 95 | 55 | 1.97 |
| 14 | Guiying Lu | 3 | 3 | 554 | 142 | 1.94 |
| 15 | Sailor Shift | 38 | 25 | 48 | 0 | 1.79 |
| 16 | Brittany Meyers | 1 | 1 | 528 | 141 | 1.78 |
| 17 | Corey Moody | 1 | 1 | 528 | 141 | 1.78 |
| 18 | Kristina Willis | 1 | 1 | 528 | 141 | 1.78 |
| 19 | Lisa Evans | 1 | 1 | 528 | 141 | 1.78 |
| 20 | Peter Huff | 1 | 1 | 528 | 141 | 1.78 |
| 21 | Susan Richardson | 1 | 1 | 528 | 141 | 1.78 |
| 22 | Thomas Kelly | 1 | 1 | 528 | 141 | 1.78 |
| 23 | Gang Chen | 11 | 11 | 392 | 84 | 1.76 |
| 24 | Ante Reinhardt-Hande | 4 | 4 | 483 | 116 | 1.72 |
| 25 | Jing Cui | 22 | 22 | 193 | 26 | 1.68 |
| 26 | Szymon Pyć | 26 | 26 | 45 | 29 | 1.67 |
| 27 | Guiying Cai | 3 | 3 | 480 | 116 | 1.66 |
| 28 | Yang Zhao | 20 | 20 | 216 | 33 | 1.65 |
| 29 | Tao Yang | 20 | 19 | 184 | 40 | 1.61 |
| 30 | Fang Zou | 17 | 17 | 198 | 52 | 1.57 |
| 31 | Megan Bennett | 21 | 21 | 54 | 49 | 1.53 |
| 32 | Andrew Williams | 23 | 23 | 38 | 35 | 1.53 |
| 33 | Maik Mude | 19 | 19 | 77 | 53 | 1.49 |
| 34 | Catherine Clay | 22 | 21 | 52 | 34 | 1.46 |
| 35 | Matthew Hancock | 21 | 21 | 58 | 36 | 1.46 |
| 36 | Na Ren | 13 | 13 | 255 | 54 | 1.46 |
| 37 | Qiang Tang | 20 | 19 | 151 | 17 | 1.41 |
| 38 | Min Lei | 20 | 20 | 133 | 15 | 1.40 |
| 39 | Yong Zheng | 22 | 20 | 47 | 25 | 1.37 |
| 40 | Bekir Bruder | 14 | 14 | 187 | 46 | 1.35 |
| 41 | Chao Wu | 13 | 12 | 235 | 46 | 1.34 |
| 42 | Lei Yuan | 16 | 16 | 149 | 30 | 1.30 |
| 43 | Yang Peng | 15 | 14 | 138 | 43 | 1.27 |
| 44 | Guiying Bai | 19 | 18 | 64 | 25 | 1.26 |
| 45 | Deborah Lucas | 15 | 15 | 91 | 45 | 1.24 |
| 46 | Urszula Stochmal | 18 | 18 | 37 | 32 | 1.23 |
| 47 | Xiuying Han | 4 | 4 | 328 | 75 | 1.21 |
| 48 | Xiuying Fan | 12 | 12 | 192 | 37 | 1.19 |
| 49 | Gerald Mullins | 16 | 14 | 112 | 31 | 1.18 |
| 50 | Brian Wright | 15 | 15 | 50 | 46 | 1.17 |
| 51 | Ming Huang | 9 | 9 | 241 | 48 | 1.17 |
| 52 | Ming Sun | 10 | 10 | 134 | 66 | 1.16 |
| 53 | Corinna Gute | 11 | 11 | 180 | 44 | 1.16 |
| 54 | Xia Wu | 15 | 13 | 111 | 35 | 1.15 |
| 55 | Jing Wang | 13 | 13 | 147 | 32 | 1.14 |
| 56 | Leyla Graf-Gotthard | 17 | 16 | 87 | 16 | 1.13 |
| 57 | Lei Duan | 17 | 16 | 95 | 13 | 1.13 |
| 58 | Min Kong | 15 | 14 | 121 | 23 | 1.12 |
| 59 | Quattro Voci | 16 | 16 | 31 | 33 | 1.12 |
| 60 | Guiying Liao | 16 | 16 | 88 | 16 | 1.11 |
| 61 | Li Lu | 13 | 12 | 86 | 47 | 1.10 |
| 62 | Jun Hao | 11 | 11 | 175 | 36 | 1.10 |
| 63 | Xiuying Yao | 13 | 12 | 139 | 31 | 1.09 |
| 64 | Gang Cui | 7 | 7 | 228 | 55 | 1.08 |
| 65 | Guiying Qin | 9 | 9 | 198 | 45 | 1.08 |
| 66 | Jing Tian | 12 | 12 | 161 | 26 | 1.07 |
| 67 | Xia Jia | 9 | 8 | 199 | 45 | 1.06 |
| 68 | Gang Zhao | 16 | 16 | 49 | 16 | 1.04 |
| 69 | Belinda Knappe | 13 | 13 | 110 | 26 | 1.04 |
| 70 | Regina Hesse | 13 | 13 | 117 | 23 | 1.03 |
| 71 | Wei Shen | 7 | 7 | 219 | 49 | 1.03 |
| 72 | Guiying Shi | 15 | 15 | 76 | 15 | 1.03 |
| 73 | Tao Gao | 16 | 16 | 68 | 7 | 1.02 |
| 74 | Joshua Herring | 14 | 12 | 91 | 28 | 1.02 |
| 75 | Xiuying Huang | 14 | 14 | 91 | 18 | 1.01 |
| 76 | Min He | 13 | 13 | 119 | 18 | 1.01 |
| 77 | Xiulan Ren | 9 | 9 | 120 | 53 | 1.00 |
| 78 | Daniël Reijers | 14 | 13 | 46 | 32 | 1.00 |
| 79 | Li Lei | 11 | 11 | 136 | 30 | 1.00 |
| 80 | Ping Zhong | 12 | 12 | 127 | 23 | 0.99 |
| 81 | Mareen Schacht | 13 | 13 | 61 | 31 | 0.99 |
| 82 | Yong Fu | 12 | 12 | 123 | 21 | 0.98 |
| 83 | Yan Tang | 11 | 11 | 139 | 25 | 0.97 |
| 84 | Yong Dong | 14 | 14 | 85 | 12 | 0.97 |
| 85 | Ming Jiang | 8 | 8 | 192 | 37 | 0.97 |
| 86 | Jie Yan | 13 | 12 | 89 | 24 | 0.96 |
| 87 | Xia Du | 14 | 14 | 79 | 13 | 0.96 |
| 88 | Jun Han | 10 | 10 | 148 | 26 | 0.94 |
| 89 | Lei Liao | 12 | 11 | 76 | 32 | 0.94 |
| 90 | Qiang Lei | 8 | 8 | 96 | 57 | 0.93 |
| 91 | Jun Dai | 11 | 11 | 128 | 21 | 0.93 |
| 92 | Ping He | 13 | 13 | 91 | 13 | 0.93 |
| 93 | Wei Liao | 10 | 10 | 146 | 24 | 0.92 |
| 94 | Juan Yin | 12 | 11 | 112 | 19 | 0.92 |
| 95 | Lei Yan | 12 | 12 | 83 | 22 | 0.91 |
| 96 | Juan Li | 12 | 12 | 82 | 22 | 0.91 |
| 97 | Xiuying Yin | 12 | 12 | 105 | 15 | 0.91 |
| 98 | Jun Yu | 12 | 12 | 112 | 13 | 0.91 |
| 99 | Marcus Spence | 13 | 12 | 43 | 26 | 0.90 |
| 100 | Ping Luo | 14 | 14 | 56 | 8 | 0.89 |
| 101 | Jie Lai | 12 | 12 | 94 | 15 | 0.89 |
| 102 | Gang Bai | 13 | 12 | 81 | 14 | 0.89 |
| 103 | Zacharie Martins | 8 | 8 | 152 | 34 | 0.88 |
| 104 | Sonic Renegade | 12 | 10 | 82 | 26 | 0.88 |
| 105 | Ping Bai | 9 | 9 | 102 | 38 | 0.88 |
| 106 | Jun Zhou | 8 | 7 | 163 | 35 | 0.88 |
| 107 | Shaan Sanghvi | 13 | 12 | 55 | 19 | 0.88 |
| 108 | Qiang Song | 12 | 11 | 99 | 16 | 0.88 |
| 109 | Yan Qin | 13 | 13 | 63 | 12 | 0.88 |
| 110 | Eugenia Mitschke | 12 | 12 | 48 | 25 | 0.87 |
| 111 | Chelsea Martinez | 13 | 13 | 45 | 16 | 0.87 |
| 112 | Jun Xia | 11 | 11 | 102 | 18 | 0.87 |
| 113 | Xia Zeng | 12 | 12 | 90 | 12 | 0.86 |
| 114 | Li Yang | 12 | 12 | 92 | 11 | 0.86 |
| 115 | Qiang Dong | 6 | 6 | 186 | 39 | 0.86 |
| 116 | Lei Xue | 13 | 13 | 67 | 8 | 0.86 |
| 117 | Yuta Tanaka | 11 | 11 | 61 | 27 | 0.85 |
| 118 | Juan Zhong | 10 | 10 | 123 | 19 | 0.85 |
| 119 | Arctic Scholars | 9 | 8 | 73 | 46 | 0.85 |
| 120 | Jun Yin | 12 | 12 | 73 | 14 | 0.85 |
| 121 | Lei Yi | 11 | 11 | 113 | 12 | 0.85 |
| 122 | Yan Zou | 11 | 11 | 94 | 17 | 0.85 |
| 123 | Guiying Kang | 8 | 8 | 140 | 31 | 0.84 |
| 124 | Lei Fu | 10 | 10 | 121 | 18 | 0.84 |
| 125 | Jun Mao | 8 | 8 | 149 | 28 | 0.84 |
| 126 | Chao Qiu | 12 | 12 | 84 | 9 | 0.84 |
| 127 | Ming Long | 11 | 11 | 76 | 20 | 0.84 |
| 128 | Li Zheng | 12 | 11 | 63 | 18 | 0.83 |
| 129 | Qiang Fang | 9 | 9 | 122 | 24 | 0.83 |
| 130 | Filippo Pelli | 11 | 10 | 91 | 19 | 0.83 |
| 131 | Guiying Pan | 11 | 11 | 93 | 13 | 0.82 |
| 132 | Li Luo | 12 | 12 | 47 | 16 | 0.82 |
| 133 | Juan Feng | 9 | 7 | 134 | 27 | 0.81 |
| 134 | Georges Besnard | 11 | 11 | 44 | 24 | 0.81 |
| 135 | Tao Sun | 11 | 11 | 81 | 13 | 0.80 |
| 136 | Jun Zou | 11 | 10 | 50 | 25 | 0.79 |
| 137 | Yan Feng | 9 | 9 | 123 | 18 | 0.79 |
| 138 | John Anderson | 8 | 7 | 114 | 34 | 0.79 |
| 139 | Alisha Fuller | 5 | 5 | 169 | 41 | 0.79 |
| 140 | Tao Dai | 12 | 12 | 58 | 8 | 0.79 |
| 141 | Peter Haering | 11 | 11 | 70 | 13 | 0.78 |
| 142 | Qiang Zhao | 11 | 11 | 66 | 14 | 0.78 |
| 143 | Fang Yin | 12 | 12 | 43 | 9 | 0.77 |
| 144 | Jun Fang | 12 | 11 | 67 | 7 | 0.77 |
| 145 | Kelly Stewart | 10 | 8 | 79 | 26 | 0.76 |
| 146 | Guiying Gao | 11 | 11 | 59 | 13 | 0.76 |
| 147 | Kimberly Castillo | 11 | 9 | 71 | 19 | 0.76 |
| 148 | Rachel Jackson | 8 | 8 | 103 | 28 | 0.76 |
| 149 | Yan Jin | 10 | 9 | 68 | 24 | 0.76 |
| 150 | Robin Webster | 10 | 10 | 43 | 26 | 0.76 |
| 151 | Jun Meng | 9 | 9 | 107 | 17 | 0.76 |
| 152 | Susan Edwards | 3 | 3 | 194 | 46 | 0.75 |
| 153 | Min Qin | 11 | 11 | 65 | 8 | 0.74 |
| 154 | Qiang Gao | 9 | 9 | 98 | 16 | 0.74 |
| 155 | Min Gao | 7 | 7 | 146 | 21 | 0.74 |
| 156 | José Berger | 4 | 4 | 163 | 43 | 0.73 |
| 157 | Adam Sanders | 1 | 1 | 240 | 49 | 0.73 |
| 158 | Christina Blair | 1 | 1 | 240 | 49 | 0.73 |
| 159 | Gabriela Campos | 1 | 1 | 240 | 49 | 0.73 |
| 160 | Noah Wilson | 1 | 1 | 240 | 49 | 0.73 |
| 161 | Tyler Brown | 1 | 1 | 240 | 49 | 0.73 |
| 162 | Min Zhao | 9 | 9 | 99 | 15 | 0.73 |
| 163 | Yang Pan | 9 | 8 | 105 | 18 | 0.73 |
| 164 | Jun Shao | 8 | 8 | 105 | 22 | 0.73 |
| 165 | Samantha Bullock | 8 | 8 | 71 | 31 | 0.73 |
| 166 | Tao Yao | 10 | 10 | 82 | 10 | 0.73 |
| 167 | Wei Ding | 10 | 9 | 47 | 24 | 0.73 |
| 168 | Ping Zeng | 11 | 11 | 52 | 9 | 0.73 |
| 169 | Min Cao | 7 | 7 | 118 | 27 | 0.73 |
| 170 | Chao Yao | 7 | 7 | 92 | 34 | 0.73 |
| 171 | Guiying Zhou | 11 | 11 | 62 | 6 | 0.73 |
| 172 | Gang Peng | 6 | 6 | 139 | 30 | 0.72 |
| 173 | Brüderklang | 2 | 2 | 212 | 46 | 0.72 |
| 174 | Tao Peng | 10 | 9 | 73 | 16 | 0.72 |
| 175 | Yan Liu | 8 | 8 | 118 | 17 | 0.72 |
| 176 | Navya Sastry | 11 | 10 | 45 | 14 | 0.72 |
| 177 | Jun Chang | 7 | 7 | 118 | 25 | 0.71 |
| 178 | Li Gu | 10 | 10 | 64 | 12 | 0.71 |
| 179 | Na Dong | 10 | 10 | 69 | 10 | 0.71 |
| 180 | Gang Shen | 11 | 11 | 50 | 6 | 0.71 |
| 181 | Lei Wang | 11 | 11 | 33 | 10 | 0.70 |
| 182 | Chao Zhu | 7 | 7 | 110 | 25 | 0.70 |
| 183 | Na Qian | 9 | 9 | 80 | 15 | 0.70 |
| 184 | Ming Duan | 6 | 6 | 119 | 31 | 0.70 |
| 185 | Ming Zhou | 9 | 9 | 81 | 14 | 0.70 |
| 186 | Gang Wan | 6 | 6 | 136 | 26 | 0.69 |
| 187 | Yan Kang | 11 | 11 | 36 | 8 | 0.69 |
| 188 | Li Song | 7 | 6 | 130 | 23 | 0.69 |
| 189 | Marilyn Moore | 2 | 2 | 194 | 46 | 0.69 |
| 190 | Qiang He | 9 | 9 | 74 | 15 | 0.69 |
| 191 | Shannon Gordon | 9 | 7 | 81 | 21 | 0.68 |
| 192 | Tao Ren | 6 | 6 | 139 | 23 | 0.68 |
| 193 | Yong Shen | 7 | 6 | 115 | 25 | 0.68 |
| 194 | Chao Zhong | 10 | 10 | 56 | 9 | 0.68 |
| 195 | Ping Liao | 10 | 10 | 56 | 9 | 0.68 |
| 196 | Li Jin | 10 | 10 | 67 | 6 | 0.68 |
| 197 | Yan Yan | 10 | 10 | 63 | 7 | 0.68 |
| 198 | Xia Dai | 10 | 10 | 51 | 10 | 0.68 |
| 199 | Yan Cai | 10 | 10 | 51 | 10 | 0.68 |
| 200 | Sandra Smith | 3 | 2 | 179 | 43 | 0.68 |
| 201 | Yong Wei | 5 | 5 | 147 | 29 | 0.68 |
| 202 | Xiulan Ye | 3 | 2 | 180 | 42 | 0.67 |
| 203 | Ming Xiang | 9 | 9 | 74 | 12 | 0.67 |
| 204 | Ming Chen | 8 | 7 | 109 | 16 | 0.67 |
| 205 | Gang Shao | 7 | 7 | 108 | 20 | 0.67 |
| 206 | Wei Zhao | 8 | 8 | 67 | 22 | 0.67 |
| 207 | Lupe Miró | 9 | 9 | 77 | 10 | 0.66 |
| 208 | Na Lai | 9 | 9 | 77 | 10 | 0.66 |
| 209 | Wayfinder's Lament | 18 | 7 | 2 | 0 | 0.66 |
| 210 | Tao Cui | 9 | 9 | 80 | 9 | 0.66 |
| 211 | Fang Su | 9 | 9 | 75 | 10 | 0.66 |
| 212 | Yan Liang | 9 | 9 | 75 | 10 | 0.66 |
| 213 | Xiuying Yuan | 7 | 7 | 108 | 19 | 0.66 |
| 214 | The Salty Wakes | 21 | 4 | 3 | 0 | 0.66 |
| 215 | Jie Cui | 9 | 9 | 70 | 11 | 0.66 |
| 216 | Theresa Rivera | 8 | 8 | 92 | 14 | 0.66 |
| 217 | Yang Cui | 9 | 9 | 73 | 10 | 0.66 |
| 218 | Ming Lei | 5 | 5 | 134 | 29 | 0.65 |
| 219 | Gianfranco Falier | 8 | 8 | 71 | 19 | 0.65 |
| 220 | Sean Jones | 9 | 8 | 47 | 21 | 0.65 |
| 221 | Gang Qin | 9 | 9 | 62 | 12 | 0.65 |
| 222 | Juan Fan | 8 | 6 | 103 | 19 | 0.65 |
| 223 | Lei Bai | 8 | 8 | 83 | 15 | 0.65 |
| 224 | Xiuying Xiang | 9 | 9 | 64 | 11 | 0.65 |
| 225 | Bradley Hayes | 8 | 8 | 49 | 24 | 0.65 |
| 226 | Dennis Lee | 8 | 8 | 49 | 24 | 0.65 |
| 227 | Rüdiger Graf | 10 | 9 | 48 | 10 | 0.64 |
| 228 | Daniel Lyons | 10 | 10 | 41 | 7 | 0.64 |
| 229 | Xiulan Yi | 9 | 9 | 59 | 11 | 0.64 |
| 230 | Xiulan Shen | 9 | 9 | 66 | 9 | 0.64 |
| 231 | Lei Tan | 6 | 6 | 121 | 21 | 0.64 |
| 232 | Jadwiga Gertz | 7 | 7 | 91 | 20 | 0.64 |
| 233 | Lei Jin | 8 | 7 | 91 | 15 | 0.63 |
| 234 | Guiying Yan | 10 | 9 | 54 | 7 | 0.63 |
| 235 | Wei Mo | 10 | 10 | 43 | 5 | 0.63 |
| 236 | Fang Tao | 8 | 8 | 91 | 10 | 0.63 |
| 237 | Li Xie | 6 | 6 | 113 | 22 | 0.63 |
| 238 | Xia Ren | 9 | 9 | 56 | 10 | 0.63 |
| 239 | Ewelina Jeszke | 8 | 8 | 40 | 23 | 0.63 |
| 240 | Ping Sun | 9 | 9 | 54 | 10 | 0.63 |
| 241 | Angelina Dallapé-Brunelleschi | 10 | 10 | 17 | 11 | 0.63 |
| 242 | Michelotto Comisso | 10 | 10 | 17 | 11 | 0.63 |
| 243 | Jie Tao | 10 | 10 | 42 | 4 | 0.62 |
| 244 | Ping Ding | 5 | 5 | 123 | 27 | 0.62 |
| 245 | Miki Hayashi | 8 | 8 | 81 | 11 | 0.62 |
| 246 | Fang Yan | 3 | 3 | 161 | 34 | 0.62 |
| 247 | Min Liao | 8 | 8 | 83 | 10 | 0.62 |
| 248 | Xiuying Zeng | 6 | 6 | 119 | 18 | 0.62 |
| 249 | Clémence Vincent | 3 | 3 | 166 | 32 | 0.61 |
| 250 | Laura Turner | 7 | 7 | 73 | 21 | 0.61 |
| 251 | Jun Jia | 5 | 5 | 121 | 26 | 0.61 |
| 252 | Min Jin | 9 | 9 | 50 | 9 | 0.61 |
| 253 | Chad Hampton | 10 | 10 | 19 | 8 | 0.61 |
| 254 | Brian Johnson | 6 | 6 | 110 | 19 | 0.61 |
| 255 | Emily Nelson | 8 | 8 | 65 | 13 | 0.61 |
| 256 | Xiulan Zeng | 10 | 9 | 34 | 8 | 0.61 |
| 257 | Guiying Dai | 6 | 6 | 109 | 19 | 0.61 |
| 258 | Alla Lorch | 10 | 10 | 16 | 8 | 0.61 |
| 259 | Sandro Gröttner | 10 | 10 | 16 | 8 | 0.61 |
| 260 | Qiang Lu | 9 | 9 | 56 | 6 | 0.60 |
| 261 | Vanessa Ramos | 7 | 7 | 88 | 15 | 0.60 |
| 262 | Cristian Bonilla | 9 | 9 | 39 | 10 | 0.60 |
| 263 | Juan Shi | 8 | 8 | 72 | 10 | 0.60 |
| 264 | Tao Ye | 7 | 7 | 79 | 17 | 0.60 |
| 265 | Ping Mo | 8 | 8 | 75 | 9 | 0.60 |
| 266 | Xia Cui | 8 | 8 | 63 | 12 | 0.60 |
| 267 | Ming Qiao | 7 | 7 | 81 | 16 | 0.60 |
| 268 | Xiulan Xue | 9 | 9 | 58 | 4 | 0.60 |
| 269 | Joseph Vargas | 1 | 1 | 209 | 35 | 0.59 |
| 270 | Keith Harrison | 1 | 1 | 209 | 35 | 0.59 |
| 271 | Donna Caldwell | 2 | 1 | 170 | 41 | 0.59 |
| 272 | Juan Jia | 7 | 7 | 85 | 14 | 0.59 |
| 273 | Na Zhou | 10 | 9 | 27 | 7 | 0.59 |
| 274 | Xiuying Ding | 10 | 8 | 39 | 8 | 0.59 |
| 275 | Yan Long | 9 | 9 | 36 | 8 | 0.58 |
| 276 | Vidur Kapadia | 9 | 9 | 16 | 13 | 0.58 |
| 277 | SideShift | 6 | 6 | 97 | 18 | 0.58 |
| 278 | Yang Ye | 7 | 7 | 82 | 13 | 0.58 |
| 279 | Min Qian | 8 | 8 | 67 | 8 | 0.58 |
| 280 | Cindy Lübs | 7 | 7 | 74 | 15 | 0.58 |
| 281 | Chao Zeng | 7 | 7 | 77 | 14 | 0.58 |
| 282 | Xiuying Song | 8 | 8 | 58 | 10 | 0.58 |
| 283 | Na Shao | 8 | 8 | 69 | 7 | 0.58 |
| 284 | Fang Xiong | 4 | 4 | 128 | 27 | 0.58 |
| 285 | Ida Hentschel | 6 | 6 | 87 | 20 | 0.58 |
| 286 | Gang Fan | 7 | 7 | 90 | 10 | 0.57 |
| 287 | Thibault Potier | 7 | 7 | 53 | 20 | 0.57 |
| 288 | Jie Fan | 7 | 6 | 88 | 15 | 0.57 |
| 289 | Min Deng | 8 | 8 | 56 | 10 | 0.57 |
| 290 | Radical Syntax | 7 | 7 | 66 | 16 | 0.57 |
| 291 | Jie Huang | 4 | 4 | 121 | 28 | 0.57 |
| 292 | Yan Shi | 9 | 9 | 39 | 5 | 0.57 |
| 293 | Wei Gao | 7 | 7 | 72 | 14 | 0.57 |
| 294 | Li Duan | 4 | 4 | 120 | 28 | 0.57 |
| 295 | Yang Chang | 6 | 6 | 94 | 17 | 0.57 |
| 296 | Yong Meng | 5 | 5 | 94 | 26 | 0.57 |
| 297 | Tao Xie | 8 | 8 | 51 | 10 | 0.56 |
| 298 | Michael Boyd | 8 | 7 | 31 | 20 | 0.56 |
| 299 | Lei Gong | 7 | 7 | 69 | 14 | 0.56 |
| 300 | Wei Xiong | 8 | 8 | 65 | 6 | 0.56 |
| 301 | Gang Wen | 9 | 8 | 48 | 6 | 0.56 |
| 302 | Cynthia Dixon | 8 | 8 | 53 | 9 | 0.56 |
| 303 | Chao Yi | 7 | 7 | 81 | 10 | 0.56 |
| 304 | Xiuying Tang | 8 | 8 | 66 | 5 | 0.56 |
| 305 | Jun Jiang | 7 | 7 | 84 | 9 | 0.56 |
| 306 | Min Duan | 9 | 7 | 62 | 6 | 0.56 |
| 307 | Yan Lin | 8 | 8 | 57 | 7 | 0.56 |
| 308 | Roy Tschentscher | 7 | 7 | 57 | 16 | 0.56 |
| 309 | Tao Lei | 8 | 8 | 56 | 7 | 0.55 |
| 310 | Yong Lin | 8 | 6 | 82 | 9 | 0.55 |
| 311 | Li Ma | 8 | 8 | 51 | 8 | 0.55 |
| 312 | Na Fan | 8 | 8 | 51 | 8 | 0.55 |
| 313 | Juan Pan | 6 | 6 | 91 | 15 | 0.55 |
| 314 | Nordic Kitchen Collective | 7 | 7 | 65 | 13 | 0.55 |
| 315 | Keith Larsen | 3 | 3 | 124 | 33 | 0.55 |
| 316 | Guiying Ren | 8 | 8 | 52 | 7 | 0.55 |
| 317 | Lucrezia Zamengo | 9 | 9 | 15 | 8 | 0.55 |
| 318 | Min Yu | 6 | 4 | 112 | 18 | 0.55 |
| 319 | Li Wan | 8 | 8 | 59 | 5 | 0.55 |
| 320 | Jun Cao | 8 | 8 | 44 | 9 | 0.55 |
| 321 | Xiuying Zhu | 4 | 4 | 114 | 26 | 0.55 |
| 322 | Bobby Tucker | 2 | 2 | 162 | 31 | 0.55 |
| 323 | Christopher Reese | 2 | 2 | 162 | 31 | 0.55 |
| 324 | Daniel Lee | 2 | 2 | 162 | 31 | 0.55 |
| 325 | Leon Hutchinson | 2 | 2 | 162 | 31 | 0.55 |
| 326 | Melanie Bautista | 2 | 2 | 162 | 31 | 0.55 |
| 327 | Rémy-Bertrand Bailly | 2 | 2 | 162 | 31 | 0.55 |
| 328 | Xiuying Dai | 6 | 6 | 88 | 15 | 0.55 |
| 329 | Li Lin | 8 | 8 | 51 | 7 | 0.55 |
| 330 | Ochre | 9 | 9 | 16 | 7 | 0.54 |
| 331 | Ekkehard Förster | 9 | 9 | 12 | 8 | 0.54 |
| 332 | Wei Yuan | 7 | 7 | 60 | 13 | 0.54 |
| 333 | Jun Ye | 7 | 7 | 63 | 12 | 0.54 |
| 334 | Xiulan Lu | 9 | 9 | 37 | 1 | 0.54 |
| 335 | Kashvi Dhillon | 8 | 7 | 39 | 14 | 0.54 |
| 336 | Tao Zhang | 8 | 8 | 47 | 7 | 0.54 |
| 337 | Juan Wu | 8 | 8 | 50 | 6 | 0.54 |
| 338 | Xiuying Li | 7 | 7 | 68 | 10 | 0.54 |
| 339 | Kathryn Golden | 7 | 6 | 74 | 13 | 0.54 |
| 340 | Fang Zhong | 7 | 6 | 70 | 14 | 0.54 |
| 341 | Fang Lin | 6 | 6 | 82 | 15 | 0.54 |
| 342 | Yang Tang | 8 | 8 | 55 | 4 | 0.53 |
| 343 | Xiuying Zhang | 5 | 5 | 99 | 19 | 0.53 |
| 344 | Jing Jin | 9 | 7 | 44 | 7 | 0.53 |
| 345 | Li Bai | 6 | 6 | 91 | 12 | 0.53 |
| 346 | Qiang Shen | 2 | 2 | 146 | 33 | 0.53 |
| 347 | Chao Tian | 7 | 7 | 57 | 12 | 0.53 |
| 348 | Zenith Horizon | 6 | 6 | 49 | 23 | 0.53 |
| 349 | Xiulan Gong | 7 | 7 | 67 | 9 | 0.53 |
| 350 | Xiuying Xie | 5 | 5 | 89 | 21 | 0.53 |
| 351 | Na Wen | 7 | 7 | 63 | 10 | 0.53 |
| 352 | Florian van Santen-Sanders | 8 | 8 | 44 | 6 | 0.53 |
| 353 | Na Peng | 8 | 7 | 63 | 5 | 0.53 |
| 354 | Ping Fu | 3 | 3 | 127 | 28 | 0.52 |
| 355 | Chao Wan | 8 | 8 | 38 | 7 | 0.52 |
| 356 | Tao Xu | 6 | 6 | 86 | 12 | 0.52 |
| 357 | Xiulan Tao | 7 | 7 | 60 | 10 | 0.52 |
| 358 | Yan Yin | 5 | 5 | 56 | 29 | 0.52 |
| 359 | Xiulan Zhao | 8 | 8 | 44 | 5 | 0.52 |
| 360 | Yan Tian | 6 | 6 | 77 | 14 | 0.52 |
| 361 | Jun Lin | 5 | 5 | 88 | 20 | 0.52 |
| 362 | Xia Li | 8 | 8 | 51 | 3 | 0.52 |
| 363 | Thomas Weber | 4 | 4 | 88 | 29 | 0.52 |
| 364 | David Wilcox | 8 | 7 | 26 | 14 | 0.52 |
| 365 | John Ferguson | 3 | 3 | 116 | 30 | 0.52 |
| 366 | Ismet Heser | 7 | 6 | 22 | 24 | 0.52 |
| 367 | Ming Ding | 8 | 8 | 45 | 4 | 0.52 |
| 368 | Xiulan Liao | 5 | 5 | 92 | 18 | 0.52 |
| 369 | Jie Zheng | 8 | 8 | 40 | 5 | 0.52 |
| 370 | Yan Xiong | 6 | 6 | 84 | 11 | 0.51 |
| 371 | Przemysław Grupa | 4 | 4 | 58 | 36 | 0.51 |
| 372 | Na Jia | 6 | 6 | 80 | 12 | 0.51 |
| 373 | Ming Xia | 3 | 3 | 128 | 26 | 0.51 |
| 374 | Yan Wen | 8 | 8 | 35 | 6 | 0.51 |
| 375 | Qiang Lai | 6 | 6 | 46 | 21 | 0.51 |
| 376 | Aimée van Dijk | 7 | 7 | 49 | 11 | 0.51 |
| 377 | Hans Josef Haering | 2 | 2 | 134 | 33 | 0.51 |
| 378 | Juan Fu | 7 | 7 | 56 | 9 | 0.51 |
| 379 | Min Long | 7 | 7 | 59 | 8 | 0.51 |
| 380 | Na Pan | 7 | 7 | 59 | 8 | 0.51 |
| 381 | Christopher Smith | 8 | 8 | 22 | 9 | 0.51 |
| 382 | Na Zhong | 8 | 8 | 33 | 6 | 0.51 |
| 383 | Adam Davis | 5 | 5 | 40 | 31 | 0.51 |
| 384 | Yong Lei | 7 | 7 | 62 | 7 | 0.51 |
| 385 | Constance Guibert | 3 | 3 | 117 | 28 | 0.51 |
| 386 | Ignazio Pastine | 3 | 3 | 117 | 28 | 0.51 |
| 387 | Tao Zeng | 7 | 7 | 54 | 9 | 0.51 |
| 388 | Guiying Song | 4 | 4 | 101 | 23 | 0.51 |
| 389 | Jun Zhang | 6 | 6 | 71 | 13 | 0.51 |
| 390 | Tonya Brown | 6 | 6 | 57 | 16 | 0.50 |
| 391 | Wei Wan | 7 | 6 | 69 | 8 | 0.50 |
| 392 | Allison Patterson | 5 | 4 | 80 | 23 | 0.50 |
| 393 | Yan Xue | 5 | 5 | 85 | 17 | 0.50 |
| 394 | Samuel Rogers | 6 | 6 | 69 | 12 | 0.50 |
| 395 | Jun Xu | 3 | 3 | 113 | 27 | 0.50 |
| 396 | Tao Jin | 7 | 7 | 50 | 8 | 0.50 |
| 397 | Fang Wu | 6 | 6 | 72 | 11 | 0.49 |
| 398 | Xiulan Sun | 8 | 8 | 38 | 2 | 0.49 |
| 399 | Fang Bai | 6 | 5 | 44 | 23 | 0.49 |
| 400 | Yang Zhang | 6 | 6 | 71 | 11 | 0.49 |
| 401 | Xiuying Cheng | 7 | 7 | 45 | 9 | 0.49 |
| 402 | Andrew Green | 1 | 1 | 162 | 31 | 0.49 |
| 403 | Eric Bailey | 1 | 1 | 162 | 31 | 0.49 |
| 404 | Inès Lebreton | 1 | 1 | 162 | 31 | 0.49 |
| 405 | Lei Zhou | 7 | 7 | 51 | 7 | 0.49 |
| 406 | Jana Lindner | 8 | 8 | 14 | 8 | 0.49 |
| 407 | Juan Qiao | 6 | 6 | 43 | 18 | 0.49 |
| 408 | Li Liao | 7 | 6 | 56 | 10 | 0.49 |
| 409 | Qiang Shi | 7 | 7 | 61 | 4 | 0.49 |
| 410 | Xiulan Li | 6 | 6 | 68 | 11 | 0.49 |
| 411 | Qiang Bai | 8 | 8 | 31 | 3 | 0.49 |
| 412 | Xiulan Shi | 7 | 7 | 31 | 12 | 0.49 |
| 413 | Isabella Farinelli | 6 | 5 | 73 | 14 | 0.49 |
| 414 | Xiulan Liang | 7 | 7 | 48 | 7 | 0.49 |
| 415 | Yan Han | 5 | 5 | 76 | 17 | 0.48 |
| 416 | Min Hu | 6 | 6 | 61 | 12 | 0.48 |
| 417 | Yong Tao | 6 | 6 | 72 | 9 | 0.48 |
| 418 | Burrowing Rodent | 5 | 5 | 68 | 19 | 0.48 |
| 419 | Michelangelo Nolcini | 5 | 5 | 68 | 19 | 0.48 |
| 420 | Rita Iannucci | 5 | 5 | 68 | 19 | 0.48 |
| 421 | Jing Zhang | 8 | 7 | 37 | 5 | 0.48 |
| 422 | Min Jia | 8 | 7 | 37 | 5 | 0.48 |
| 423 | Xiulan Yao | 6 | 6 | 64 | 11 | 0.48 |
| 424 | Jun Wan | 8 | 8 | 27 | 3 | 0.48 |
| 425 | Yan Su | 7 | 7 | 49 | 6 | 0.48 |
| 426 | Chao Qiao | 6 | 6 | 60 | 12 | 0.48 |
| 427 | Guiying Ding | 5 | 5 | 89 | 13 | 0.48 |
| 428 | Na Deng | 8 | 7 | 39 | 4 | 0.48 |
| 429 | Lei Shen | 6 | 6 | 57 | 12 | 0.48 |
| 430 | Gang He | 8 | 8 | 31 | 1 | 0.48 |
| 431 | Karen Wright | 7 | 7 | 27 | 11 | 0.48 |
| 432 | Li Long | 6 | 6 | 52 | 13 | 0.47 |
| 433 | Jie Jiang | 8 | 7 | 43 | 2 | 0.47 |
| 434 | Jun Qiao | 7 | 7 | 48 | 5 | 0.47 |
| 435 | Jun Liang | 4 | 4 | 99 | 18 | 0.47 |
| 436 | Tao Liao | 6 | 6 | 69 | 8 | 0.47 |
| 437 | Xiuying Dong | 7 | 7 | 43 | 6 | 0.47 |
| 438 | Jing Pan | 6 | 5 | 71 | 12 | 0.47 |
| 439 | Nathan Bryant | 5 | 5 | 76 | 15 | 0.47 |
| 440 | Xia Lin | 8 | 7 | 32 | 4 | 0.47 |
| 441 | Yong Yao | 7 | 7 | 37 | 7 | 0.47 |
| 442 | Xiulan Qin | 7 | 7 | 48 | 4 | 0.47 |
| 443 | Tao Bai | 7 | 6 | 54 | 7 | 0.47 |
| 444 | Yong Wen | 6 | 6 | 70 | 7 | 0.47 |
| 445 | Na Ma | 6 | 6 | 55 | 11 | 0.47 |
| 446 | Dora Säuberlich | 1 | 1 | 140 | 33 | 0.47 |
| 447 | Jun Duan | 5 | 5 | 77 | 14 | 0.47 |
| 448 | Jonathan Poole | 7 | 7 | 25 | 10 | 0.47 |
| 449 | Interval Shift | 7 | 7 | 36 | 7 | 0.47 |
| 450 | Martino Michelangeli | 7 | 7 | 36 | 7 | 0.47 |
| 451 | Jing Guo | 7 | 7 | 47 | 4 | 0.47 |
| 452 | Xiulan Hou | 6 | 6 | 56 | 10 | 0.46 |
| 453 | Ping Xia | 7 | 7 | 30 | 8 | 0.46 |
| 454 | John Ramirez | 4 | 3 | 58 | 32 | 0.46 |
| 455 | Li Gong | 8 | 8 | 26 | 0 | 0.46 |
| 456 | Jie Shao | 4 | 4 | 92 | 18 | 0.46 |
| 457 | Erdogan Baum | 5 | 5 | 73 | 14 | 0.46 |
| 458 | Gang Zheng | 5 | 5 | 73 | 14 | 0.46 |
| 459 | Borys Kościk | 8 | 8 | 10 | 4 | 0.46 |
| 460 | Brandon Bartlett | 5 | 5 | 69 | 15 | 0.46 |
| 461 | Lunar Syntax | 5 | 5 | 69 | 15 | 0.46 |
| 462 | Na Guo | 7 | 7 | 43 | 4 | 0.46 |
| 463 | Jun Yi | 6 | 6 | 54 | 10 | 0.46 |
| 464 | The Wandering Pulse | 7 | 7 | 17 | 11 | 0.46 |
| 465 | Qiang Yang | 6 | 6 | 65 | 7 | 0.46 |
| 466 | Jie Wen | 5 | 5 | 65 | 16 | 0.46 |
| 467 | Tarini Hans | 7 | 6 | 34 | 11 | 0.46 |
| 468 | Ping Cai | 5 | 5 | 76 | 13 | 0.46 |
| 469 | Ping Pan | 4 | 4 | 87 | 19 | 0.46 |
| 470 | Wei Cai | 4 | 4 | 94 | 17 | 0.46 |
| 471 | Fang Duan | 6 | 6 | 57 | 9 | 0.46 |
| 472 | Lei Qiu | 6 | 5 | 63 | 12 | 0.46 |
| 473 | Qiang Cui | 7 | 7 | 42 | 4 | 0.46 |
| 474 | Xiulan He | 6 | 6 | 53 | 10 | 0.46 |
| 475 | Nordic Echo | 6 | 5 | 33 | 20 | 0.46 |
| 476 | Min Ye | 6 | 6 | 37 | 14 | 0.45 |
| 477 | Lei Hu | 6 | 6 | 59 | 8 | 0.45 |
| 478 | Juan Du | 4 | 4 | 81 | 20 | 0.45 |
| 479 | Katrin Steckel | 1 | 1 | 132 | 33 | 0.45 |
| 480 | Roswita Hande | 1 | 1 | 132 | 33 | 0.45 |
| 481 | Kaitlyn Warren | 5 | 5 | 39 | 22 | 0.45 |
| 482 | Linda Reed | 8 | 7 | 15 | 6 | 0.45 |
| 483 | Ming Cui | 6 | 6 | 64 | 6 | 0.45 |
| 484 | Guiying Hou | 7 | 7 | 38 | 4 | 0.45 |
| 485 | Gang Yuan | 7 | 7 | 34 | 5 | 0.45 |
| 486 | Min Xiang | 6 | 6 | 67 | 5 | 0.45 |
| 487 | Xia Xiong | 6 | 6 | 55 | 8 | 0.45 |
| 488 | Guiying Zeng | 7 | 7 | 40 | 3 | 0.45 |
| 489 | Drowned Harbor | 12 | 5 | 4 | 0 | 0.45 |
| 490 | Liliana Heidrich | 4 | 4 | 106 | 12 | 0.45 |
| 491 | Xiuying Meng | 7 | 5 | 55 | 8 | 0.45 |
| 492 | Wei Tang | 8 | 7 | 19 | 4 | 0.45 |
| 493 | Laetitia Bertrand-Becker | 7 | 7 | 24 | 7 | 0.45 |
| 494 | Jun Guo | 6 | 6 | 57 | 7 | 0.45 |
| 495 | Gang Yang | 7 | 6 | 48 | 5 | 0.44 |
| 496 | Zachary Harris | 7 | 6 | 33 | 9 | 0.44 |
| 497 | Yong Su | 7 | 6 | 44 | 6 | 0.44 |
| 498 | Jie Xu | 6 | 5 | 77 | 6 | 0.44 |
| 499 | Tao Yin | 8 | 7 | 25 | 2 | 0.44 |
| 500 | Lei Tang | 8 | 6 | 34 | 4 | 0.44 |
| 501 | Juan Duan | 5 | 5 | 70 | 12 | 0.44 |
| 502 | Ming Kang | 4 | 4 | 70 | 21 | 0.44 |
| 503 | Juan Kang | 7 | 7 | 33 | 4 | 0.44 |
| 504 | Juan Yao | 7 | 6 | 50 | 4 | 0.44 |
| 505 | Mia Carsten | 5 | 5 | 66 | 13 | 0.44 |
| 506 | Nathan Perez | 5 | 5 | 69 | 12 | 0.44 |
| 507 | Bryan Smith | 6 | 6 | 50 | 8 | 0.44 |
| 508 | Xiuying Kong | 4 | 4 | 109 | 10 | 0.44 |
| 509 | Lei He | 7 | 7 | 35 | 3 | 0.44 |
| 510 | Ping Lai | 3 | 3 | 105 | 20 | 0.44 |
| 511 | Na Cui | 5 | 4 | 74 | 15 | 0.44 |
| 512 | Yang Yu | 7 | 7 | 31 | 4 | 0.44 |
| 513 | Min Li | 7 | 6 | 48 | 4 | 0.44 |
| 514 | Na Su | 5 | 5 | 75 | 10 | 0.44 |
| 515 | Min Mo | 7 | 6 | 36 | 7 | 0.44 |
| 516 | Juan Yu | 6 | 5 | 58 | 10 | 0.44 |
| 517 | Lei Wan | 3 | 3 | 100 | 21 | 0.44 |
| 518 | Ping Jia | 5 | 5 | 66 | 12 | 0.44 |
| 519 | Ming Ren | 6 | 6 | 51 | 7 | 0.44 |
| 520 | Xiulan Wei | 6 | 6 | 51 | 7 | 0.44 |
| 521 | Xia Ding | 5 | 5 | 62 | 13 | 0.43 |
| 522 | Wei Luo | 7 | 7 | 36 | 2 | 0.43 |
| 523 | Qiang Dai | 6 | 6 | 47 | 8 | 0.43 |
| 524 | Mike Robinson | 4 | 4 | 80 | 17 | 0.43 |
| 525 | Lei Luo | 6 | 6 | 54 | 6 | 0.43 |
| 526 | Dwayne Wilson | 7 | 7 | 28 | 4 | 0.43 |
| 527 | Wei Shi | 6 | 6 | 50 | 7 | 0.43 |
| 528 | Barbara Weitzel | 4 | 4 | 61 | 22 | 0.43 |
| 529 | Li Deng | 7 | 6 | 41 | 5 | 0.43 |
| 530 | Brandi Rodriguez | 5 | 5 | 35 | 20 | 0.43 |
| 531 | Na Lu | 3 | 3 | 105 | 19 | 0.43 |
| 532 | Ping Song | 7 | 7 | 31 | 3 | 0.43 |
| 533 | Xia Chen | 7 | 7 | 31 | 3 | 0.43 |
| 534 | Xia Xue | 6 | 6 | 42 | 9 | 0.43 |
| 535 | Tao Su | 6 | 6 | 53 | 6 | 0.43 |
| 536 | Silvio Krause | 7 | 7 | 16 | 7 | 0.43 |
| 537 | Gang Tan | 7 | 7 | 34 | 2 | 0.43 |
| 538 | Jing Long | 6 | 6 | 52 | 6 | 0.43 |
| 539 | Jing Lin | 5 | 5 | 63 | 12 | 0.43 |
| 540 | Xiulan Lin | 6 | 6 | 48 | 7 | 0.43 |
| 541 | Tao Hu | 6 | 6 | 44 | 8 | 0.43 |
| 542 | Xiuying Ye | 6 | 6 | 55 | 5 | 0.43 |
| 543 | Angelina Sölzer | 5 | 5 | 55 | 14 | 0.43 |
| 544 | Denise Bell | 5 | 5 | 40 | 18 | 0.43 |
| 545 | Janice Lamb | 6 | 6 | 25 | 13 | 0.43 |
| 546 | Jie Su | 7 | 7 | 36 | 1 | 0.43 |
| 547 | Xia Zhu | 6 | 6 | 47 | 7 | 0.43 |
| 548 | Xiulan Dong | 6 | 6 | 47 | 7 | 0.43 |
| 549 | Yong Wang | 6 | 6 | 43 | 8 | 0.43 |
| 550 | Xiulan Yan | 6 | 6 | 46 | 7 | 0.43 |
| 551 | Nada Pechel | 4 | 4 | 68 | 19 | 0.43 |
| 552 | Ping Hao | 7 | 7 | 27 | 3 | 0.43 |
| 553 | David Wilkerson | 8 | 7 | 7 | 4 | 0.43 |
| 554 | Audrey-Camille Nicolas | 8 | 7 | 10 | 3 | 0.42 |
| 555 | Fang Cui | 5 | 4 | 69 | 14 | 0.42 |
| 556 | Gang Pan | 7 | 7 | 22 | 4 | 0.42 |
| 557 | Christine Gonzales | 6 | 6 | 44 | 7 | 0.42 |
| 558 | Fang Kong | 6 | 6 | 44 | 7 | 0.42 |
| 559 | Wei Du | 4 | 4 | 55 | 22 | 0.42 |
| 560 | Juan Zou | 6 | 6 | 47 | 6 | 0.42 |
| 561 | Chao Yu | 6 | 6 | 58 | 3 | 0.42 |
| 562 | Xiuying Fang | 7 | 6 | 38 | 4 | 0.42 |
| 563 | Gang Yin | 6 | 6 | 43 | 7 | 0.42 |
| 564 | Starseed | 5 | 5 | 54 | 13 | 0.42 |
| 565 | Yan Qiu | 7 | 6 | 45 | 2 | 0.42 |
| 566 | Juan Xiong | 4 | 4 | 83 | 14 | 0.42 |
| 567 | Lorraine Martinez | 7 | 7 | 20 | 4 | 0.42 |
| 568 | Chao Xiao | 6 | 6 | 42 | 7 | 0.42 |
| 569 | Guiying Shao | 5 | 5 | 64 | 10 | 0.42 |
| 570 | Gino Michelangeli | 6 | 6 | 38 | 8 | 0.42 |
| 571 | Midnight Protocol | 2 | 2 | 108 | 25 | 0.42 |
| 572 | Lei Yang | 6 | 6 | 41 | 7 | 0.42 |
| 573 | Orla Seabloom | 8 | 8 | 0 | 0 | 0.42 |
| 574 | Yong Yan | 6 | 6 | 40 | 7 | 0.42 |
| 575 | Li Zeng | 6 | 6 | 43 | 6 | 0.42 |
| 576 | Ping Xiang | 6 | 6 | 39 | 7 | 0.41 |
| 577 | Clayton Reed | 6 | 6 | 24 | 11 | 0.41 |
| 578 | Chao Zhao | 6 | 6 | 46 | 5 | 0.41 |
| 579 | Fang Mao | 7 | 7 | 20 | 3 | 0.41 |
| 580 | Ming Yao | 7 | 7 | 31 | 0 | 0.41 |
| 581 | Qiang Gu | 6 | 6 | 42 | 6 | 0.41 |
| 582 | Fang Zhou | 6 | 5 | 55 | 7 | 0.41 |
| 583 | Juan Jin | 5 | 5 | 60 | 10 | 0.41 |
| 584 | Ivy Echos | 11 | 4 | 13 | 1 | 0.41 |
| 585 | Donald Choi | 5 | 5 | 48 | 13 | 0.41 |
| 586 | Guiying Huang | 4 | 4 | 77 | 14 | 0.41 |
| 587 | Yong Jia | 6 | 6 | 51 | 3 | 0.41 |
| 588 | Jun Ding | 4 | 4 | 62 | 18 | 0.41 |
| 589 | Melanie Jimenez | 7 | 7 | 10 | 5 | 0.41 |
| 590 | Jun Xie | 6 | 6 | 39 | 6 | 0.41 |
| 591 | Ping Qin | 6 | 6 | 39 | 6 | 0.41 |
| 592 | Jing Lai | 5 | 5 | 57 | 10 | 0.41 |
| 593 | Tao Hou | 5 | 5 | 57 | 10 | 0.41 |
| 594 | Yang He | 5 | 5 | 68 | 7 | 0.41 |
| 595 | Chao Wei | 6 | 6 | 38 | 6 | 0.41 |
| 596 | Jie Zhang | 6 | 6 | 38 | 6 | 0.41 |
| 597 | Kayla Scott | 3 | 3 | 86 | 20 | 0.41 |
| 598 | Leo Eberth | 6 | 5 | 51 | 7 | 0.41 |
| 599 | Robert Knight | 5 | 5 | 56 | 10 | 0.41 |
| 600 | Fang Lu | 5 | 5 | 67 | 7 | 0.41 |
| 601 | Yan Zhou | 7 | 6 | 35 | 2 | 0.40 |
| 602 | Gang Cao | 5 | 5 | 51 | 11 | 0.40 |
| 603 | David Armstrong | 6 | 6 | 36 | 6 | 0.40 |
| 604 | Xiulan Mo | 6 | 6 | 43 | 4 | 0.40 |
| 605 | Patricia Humphrey | 2 | 1 | 115 | 25 | 0.40 |
| 606 | Vera Rivero Palomo | 2 | 2 | 94 | 26 | 0.40 |
| 607 | Yolanda Barroso Pineda | 2 | 2 | 94 | 26 | 0.40 |
| 608 | Kelsey Campbell | 6 | 6 | 27 | 8 | 0.40 |
| 609 | Jie Zhu | 6 | 6 | 38 | 5 | 0.40 |
| 610 | Fang Chen | 6 | 6 | 34 | 6 | 0.40 |
| 611 | Na Yang | 5 | 5 | 56 | 9 | 0.40 |
| 612 | Xiulan Liu | 4 | 4 | 78 | 12 | 0.40 |
| 613 | Wei Han | 6 | 5 | 47 | 7 | 0.40 |
| 614 | Xiuying Cai | 5 | 3 | 75 | 13 | 0.40 |
| 615 | Tao Fang | 6 | 6 | 37 | 5 | 0.40 |
| 616 | Matthew Griffin | 5 | 5 | 48 | 11 | 0.40 |
| 617 | Min Wen | 5 | 5 | 59 | 8 | 0.40 |
| 618 | Wei Wang | 5 | 5 | 59 | 8 | 0.40 |
| 619 | Yang Gu | 6 | 6 | 44 | 3 | 0.40 |
| 620 | Ping Li | 5 | 5 | 62 | 7 | 0.40 |
| 621 | Guglielmo Canetta | 6 | 6 | 25 | 8 | 0.40 |
| 622 | Nicola Bernetti | 6 | 6 | 25 | 8 | 0.40 |
| 623 | Serena Lettiere | 6 | 6 | 25 | 8 | 0.40 |
| 624 | Vincentio Gentili | 6 | 6 | 25 | 8 | 0.40 |
| 625 | Xiuying Deng | 6 | 6 | 36 | 5 | 0.40 |
| 626 | Na Mao | 3 | 3 | 91 | 17 | 0.40 |
| 627 | Wei Su | 6 | 6 | 39 | 4 | 0.40 |
| 628 | Xia Xia | 5 | 5 | 50 | 10 | 0.40 |
| 629 | The Fiddle & The Fjord | 12 | 3 | 4 | 1 | 0.40 |
| 630 | Xiuying Qiu | 6 | 6 | 42 | 3 | 0.40 |
| 631 | Xia Fu | 7 | 7 | 16 | 1 | 0.40 |
| 632 | Francesca Maglio | 6 | 6 | 30 | 6 | 0.39 |
| 633 | Qiang Chang | 5 | 5 | 63 | 6 | 0.39 |
| 634 | Rei Ito | 4 | 4 | 74 | 12 | 0.39 |
| 635 | Min Hou | 6 | 6 | 33 | 5 | 0.39 |
| 636 | Tao Wei | 6 | 6 | 33 | 5 | 0.39 |
| 637 | Ping Yao | 5 | 5 | 33 | 14 | 0.39 |
| 638 | Gang Long | 4 | 4 | 66 | 14 | 0.39 |
| 639 | Xia Yuan | 5 | 4 | 68 | 9 | 0.39 |
| 640 | Joseph Dixon | 3 | 3 | 106 | 12 | 0.39 |
| 641 | Radiation Pulse | 3 | 3 | 106 | 12 | 0.39 |
| 642 | Ming Yan | 4 | 4 | 69 | 13 | 0.39 |
| 643 | Jing Ren | 6 | 6 | 43 | 2 | 0.39 |
| 644 | Jie Cai | 6 | 6 | 35 | 4 | 0.39 |
| 645 | Monica Brown | 5 | 5 | 57 | 7 | 0.39 |
| 646 | Jing Chang | 5 | 5 | 53 | 8 | 0.39 |
| 647 | Fang Liang | 6 | 6 | 38 | 3 | 0.39 |
| 648 | Lei Kong | 6 | 6 | 34 | 4 | 0.39 |
| 649 | Qiang Tan | 3 | 3 | 93 | 15 | 0.39 |
| 650 | Gang Dong | 4 | 3 | 73 | 16 | 0.39 |
| 651 | Jing Sun | 5 | 5 | 52 | 8 | 0.39 |
| 652 | Jing Mao | 5 | 4 | 58 | 11 | 0.39 |
| 653 | Xiuying Bai | 6 | 6 | 37 | 3 | 0.39 |
| 654 | Ping Wu | 6 | 6 | 33 | 4 | 0.39 |
| 655 | Arnaude Joseph-Lacombe | 6 | 5 | 39 | 7 | 0.39 |
| 656 | Guiying Tian | 5 | 5 | 55 | 7 | 0.39 |
| 657 | Ming Mao | 5 | 5 | 55 | 7 | 0.39 |
| 658 | Juan Xu | 5 | 4 | 61 | 10 | 0.39 |
| 659 | Yan Tan | 6 | 6 | 29 | 5 | 0.39 |
| 660 | Jing Qian | 5 | 5 | 51 | 8 | 0.39 |
| 661 | Yang Liao | 5 | 5 | 51 | 8 | 0.39 |
| 662 | Ashley Cox PhD | 4 | 4 | 69 | 12 | 0.38 |
| 663 | Blueprints | 4 | 4 | 69 | 12 | 0.38 |
| 664 | Primal Rhythm | 4 | 4 | 69 | 12 | 0.38 |
| 665 | Sara Parker | 5 | 5 | 54 | 7 | 0.38 |
| 666 | Jie Fang | 5 | 5 | 57 | 6 | 0.38 |
| 667 | Juan Mo | 5 | 4 | 48 | 13 | 0.38 |
| 668 | Chao Yang | 5 | 5 | 53 | 7 | 0.38 |
| 669 | Ming Yang | 6 | 6 | 30 | 4 | 0.38 |
| 670 | Helen Simon | 5 | 5 | 30 | 13 | 0.38 |
| 671 | Luminous Fracture | 3 | 3 | 78 | 18 | 0.38 |
| 672 | Robert Garcia | 3 | 3 | 78 | 18 | 0.38 |
| 673 | Wei Cheng | 5 | 5 | 41 | 10 | 0.38 |
| 674 | Jing Tan | 6 | 6 | 33 | 3 | 0.38 |
| 675 | Qiang Xie | 5 | 5 | 55 | 6 | 0.38 |
| 676 | Jie Cao | 7 | 6 | 24 | 1 | 0.38 |
| 677 | Ming Zhao | 6 | 4 | 52 | 7 | 0.38 |
| 678 | Monica Nelson | 5 | 5 | 51 | 7 | 0.38 |
| 679 | Heidi Jones | 4 | 4 | 62 | 13 | 0.38 |
| 680 | Min Shi | 6 | 6 | 36 | 2 | 0.38 |
| 681 | Xia Liang | 6 | 6 | 32 | 3 | 0.38 |
| 682 | Chao Li | 6 | 4 | 44 | 9 | 0.38 |
| 683 | Harro Trapp-Caspar | 5 | 5 | 28 | 13 | 0.38 |
| 684 | Gang Zhang | 5 | 5 | 50 | 7 | 0.38 |
| 685 | Ming Cheng | 6 | 5 | 41 | 5 | 0.38 |
| 686 | Yang Bai | 5 | 5 | 46 | 8 | 0.38 |
| 687 | Ping Yan | 3 | 2 | 100 | 16 | 0.38 |
| 688 | Na Kong | 5 | 5 | 57 | 5 | 0.38 |
| 689 | Juan Dong | 6 | 6 | 31 | 3 | 0.38 |
| 690 | Lei Zheng | 6 | 6 | 31 | 3 | 0.38 |
| 691 | Andrew Dawson | 4 | 4 | 42 | 18 | 0.38 |
| 692 | Xiulan Du | 6 | 6 | 38 | 1 | 0.38 |
| 693 | Juan Ding | 6 | 6 | 34 | 2 | 0.38 |
| 694 | Lei Long | 5 | 5 | 45 | 8 | 0.38 |
| 695 | Caroline Reilly | 3 | 2 | 99 | 16 | 0.38 |
| 696 | Lori Waters | 3 | 2 | 99 | 16 | 0.38 |
| 697 | Necropolis Noir | 3 | 2 | 99 | 16 | 0.38 |
| 698 | Jasmine Adams | 4 | 4 | 67 | 11 | 0.38 |
| 699 | Guiying Shen | 5 | 5 | 48 | 7 | 0.37 |
| 700 | Karl-August Beyer | 4 | 4 | 55 | 14 | 0.37 |
| 701 | Kelsey Hernandez | 6 | 6 | 29 | 3 | 0.37 |
| 702 | Yong Lu | 5 | 5 | 40 | 9 | 0.37 |
| 703 | Min Qiu | 5 | 5 | 51 | 6 | 0.37 |
| 704 | Jie Long | 6 | 6 | 25 | 4 | 0.37 |
| 705 | Qiang Zhang | 6 | 6 | 25 | 4 | 0.37 |
| 706 | Na Zou | 5 | 5 | 47 | 7 | 0.37 |
| 707 | Anthony Ortega | 3 | 3 | 58 | 22 | 0.37 |
| 708 | Lei Zhao | 6 | 6 | 32 | 2 | 0.37 |
| 709 | Erica Walton | 5 | 4 | 34 | 15 | 0.37 |
| 710 | Qiang Wu | 5 | 5 | 50 | 6 | 0.37 |
| 711 | Tobias Etzold-Dörr | 5 | 5 | 50 | 6 | 0.37 |
| 712 | Kristin Anderson | 4 | 4 | 61 | 12 | 0.37 |
| 713 | Rachel Hill | 5 | 5 | 42 | 8 | 0.37 |
| 714 | Li Yin | 5 | 5 | 53 | 5 | 0.37 |
| 715 | Denise White | 4 | 4 | 53 | 14 | 0.37 |
| 716 | Twilight Riders | 4 | 4 | 53 | 14 | 0.37 |
| 717 | Chao Han | 5 | 5 | 49 | 6 | 0.37 |
| 718 | Chao Xu | 5 | 5 | 49 | 6 | 0.37 |
| 719 | Min Su | 6 | 6 | 19 | 5 | 0.37 |
| 720 | Jing Qin | 4 | 4 | 67 | 10 | 0.37 |
| 721 | Wei Gu | 6 | 6 | 30 | 2 | 0.37 |
| 722 | Wei Feng | 1 | 1 | 111 | 25 | 0.37 |
| 723 | Ping Shen | 3 | 3 | 74 | 17 | 0.37 |
| 724 | Yang Wu | 6 | 4 | 49 | 6 | 0.37 |
| 725 | Kavya Agrawal | 3 | 3 | 37 | 27 | 0.37 |
| 726 | Cemil Linke | 2 | 2 | 85 | 23 | 0.37 |
| 727 | Fedor Bolzmann | 2 | 2 | 85 | 23 | 0.37 |
| 728 | Embers of Wrath | 1 | 1 | 107 | 26 | 0.37 |
| 729 | Anaïs Wagner | 3 | 3 | 81 | 15 | 0.37 |
| 730 | Neue Schicht | 3 | 3 | 81 | 15 | 0.37 |
| 731 | Yong Lai | 5 | 4 | 50 | 10 | 0.37 |
| 732 | Beatrice Albright | 7 | 7 | 3 | 0 | 0.37 |
| 733 | Daniel O'Connell | 7 | 7 | 3 | 0 | 0.37 |
| 734 | Ryan Doyle | 6 | 6 | 14 | 6 | 0.37 |
| 735 | The Forgotten Archives | 2 | 2 | 62 | 29 | 0.37 |
| 736 | Min Ren | 4 | 3 | 79 | 11 | 0.37 |
| 737 | Li Xue | 4 | 4 | 65 | 10 | 0.37 |
| 738 | Jie Zou | 6 | 5 | 34 | 5 | 0.37 |
| 739 | Copper Canyon Ghosts | 7 | 7 | 2 | 0 | 0.37 |
| 740 | Juan Cao | 5 | 5 | 50 | 5 | 0.37 |
| 741 | Min Huang | 5 | 5 | 50 | 5 | 0.37 |
| 742 | Juan Yang | 4 | 4 | 61 | 11 | 0.37 |
| 743 | Guiying Yao | 6 | 6 | 24 | 3 | 0.37 |
| 744 | Jing Zhong | 6 | 6 | 24 | 3 | 0.37 |
| 745 | Chao Peng | 6 | 5 | 37 | 4 | 0.36 |
| 746 | Guiying Cao | 5 | 5 | 42 | 7 | 0.36 |
| 747 | Chao Chen | 6 | 6 | 23 | 3 | 0.36 |
| 748 | Jing Yi | 5 | 5 | 41 | 7 | 0.36 |
| 749 | Jun Jin | 4 | 4 | 63 | 10 | 0.36 |
| 750 | Margarita Henschel | 5 | 5 | 33 | 9 | 0.36 |
| 751 | Fredo Grossi | 5 | 5 | 44 | 6 | 0.36 |
| 752 | Yasmin Verschut | 6 | 6 | 7 | 7 | 0.36 |
| 753 | Xia Cai | 5 | 5 | 40 | 7 | 0.36 |
| 754 | Li He | 6 | 6 | 25 | 2 | 0.36 |
| 755 | Julia Carter | 8 | 6 | 0 | 0 | 0.36 |
| 756 | Kristi Crane | 6 | 5 | 16 | 9 | 0.36 |
| 757 | Jun Song | 4 | 4 | 69 | 8 | 0.36 |
| 758 | Lei Feng | 3 | 3 | 69 | 17 | 0.36 |
| 759 | Yan Duan | 5 | 5 | 43 | 6 | 0.36 |
| 760 | Li Han | 3 | 3 | 65 | 18 | 0.36 |
| 761 | Gang Lei | 5 | 5 | 39 | 7 | 0.36 |
| 762 | Jun Pan | 5 | 5 | 39 | 7 | 0.36 |
| 763 | Xiuying Mo | 5 | 5 | 39 | 7 | 0.36 |
| 764 | Qiang Qian | 6 | 5 | 37 | 3 | 0.36 |
| 765 | Yang Hou | 6 | 6 | 27 | 1 | 0.36 |
| 766 | Jie Ding | 5 | 5 | 38 | 7 | 0.36 |
| 767 | Jakub Dziuda | 6 | 6 | 12 | 5 | 0.36 |
| 768 | Yong Cao | 5 | 5 | 45 | 5 | 0.36 |
| 769 | Yan He | 5 | 5 | 41 | 6 | 0.36 |
| 770 | Angelita Belda Enríquez | 5 | 5 | 37 | 7 | 0.36 |
| 771 | Gang Du | 6 | 5 | 28 | 5 | 0.36 |
| 772 | Cheryl Carter | 5 | 5 | 33 | 8 | 0.36 |
| 773 | Min Xiong | 5 | 5 | 44 | 5 | 0.36 |
| 774 | Min Sun | 5 | 5 | 40 | 6 | 0.35 |
| 775 | Gang Jia | 5 | 5 | 51 | 3 | 0.35 |
| 776 | Graziella Saffi | 6 | 6 | 14 | 4 | 0.35 |
| 777 | Yang Zhong | 5 | 5 | 47 | 4 | 0.35 |
| 778 | Gang Mo | 6 | 5 | 16 | 8 | 0.35 |
| 779 | Susan Anderson | 3 | 3 | 69 | 16 | 0.35 |
| 780 | Ming Zheng | 5 | 5 | 43 | 5 | 0.35 |
| 781 | Juan Song | 6 | 6 | 28 | 0 | 0.35 |
| 782 | Charles Vazquez | 5 | 5 | 39 | 6 | 0.35 |
| 783 | Liwia Olbrych | 6 | 5 | 19 | 7 | 0.35 |
| 784 | Fang Xiang | 6 | 6 | 24 | 1 | 0.35 |
| 785 | Tao Wen | 5 | 5 | 35 | 7 | 0.35 |
| 786 | Jeffery Bailey | 2 | 2 | 83 | 21 | 0.35 |
| 787 | Ping Zhou | 6 | 6 | 20 | 2 | 0.35 |
| 788 | Bartek Krężołek | 6 | 6 | 16 | 3 | 0.35 |
| 789 | Martine Normand | 6 | 6 | 12 | 4 | 0.35 |
| 790 | Li Dong | 4 | 4 | 60 | 9 | 0.35 |
| 791 | Jie Hu | 5 | 5 | 30 | 8 | 0.35 |
| 792 | Vito Stroh | 5 | 5 | 30 | 8 | 0.35 |
| 793 | Yan Zhu | 5 | 5 | 33 | 7 | 0.35 |
| 794 | Jivika Tank | 5 | 5 | 14 | 12 | 0.35 |
| 795 | Qiang Han | 6 | 6 | 21 | 1 | 0.35 |
| 796 | Laura Sanchez | 6 | 6 | 6 | 5 | 0.35 |
| 797 | Na Dai | 6 | 5 | 34 | 2 | 0.35 |
| 798 | Karina Hess | 5 | 5 | 35 | 6 | 0.35 |
| 799 | Yang Yao | 4 | 3 | 63 | 12 | 0.35 |
| 800 | Dominic Riehl | 4 | 3 | 33 | 20 | 0.35 |
| 801 | Jun Luo | 5 | 5 | 38 | 5 | 0.35 |
| 802 | Lei Cao | 6 | 6 | 19 | 1 | 0.34 |
| 803 | Yong Chen | 4 | 4 | 52 | 10 | 0.34 |
| 804 | Lisa Martin | 3 | 3 | 74 | 13 | 0.34 |
| 805 | Albert Miller | 5 | 5 | 37 | 5 | 0.34 |
| 806 | Gang Sun | 5 | 4 | 43 | 8 | 0.34 |
| 807 | Chao Fan | 6 | 5 | 35 | 1 | 0.34 |
| 808 | Yan Lu | 5 | 5 | 36 | 5 | 0.34 |
| 809 | Michelle Davis | 5 | 5 | 32 | 6 | 0.34 |
| 810 | Juan Sun | 4 | 4 | 54 | 9 | 0.34 |
| 811 | Christopher Lee | 5 | 5 | 28 | 7 | 0.34 |
| 812 | Ping Wan | 5 | 5 | 39 | 4 | 0.34 |
| 813 | Min Liang | 5 | 5 | 35 | 5 | 0.34 |
| 814 | Yong Zeng | 5 | 5 | 35 | 5 | 0.34 |
| 815 | Gang Zhou | 5 | 5 | 38 | 4 | 0.34 |
| 816 | Min Shao | 5 | 5 | 38 | 4 | 0.34 |
| 817 | Xia Deng | 4 | 4 | 38 | 13 | 0.34 |
| 818 | Yong Gao | 3 | 3 | 71 | 13 | 0.34 |
| 819 | Na Wei | 5 | 5 | 34 | 5 | 0.34 |
| 820 | Ming Xiong | 4 | 4 | 52 | 9 | 0.34 |
| 821 | Na Gu | 4 | 4 | 63 | 6 | 0.34 |
| 822 | Juan Xiao | 6 | 5 | 32 | 1 | 0.34 |
| 823 | Sarah Johnson | 3 | 3 | 74 | 12 | 0.34 |
| 824 | Xiulan Wang | 5 | 4 | 43 | 7 | 0.34 |
| 825 | The Saltwater Weavers | 9 | 4 | 4 | 0 | 0.34 |
| 826 | Xiulan Hao | 6 | 5 | 28 | 2 | 0.34 |
| 827 | Ping Jiang | 5 | 5 | 33 | 5 | 0.34 |
| 828 | Lisa Jones | 3 | 3 | 66 | 14 | 0.34 |
| 829 | Ann Holland | 1 | 1 | 99 | 23 | 0.34 |
| 830 | Eric Beasley | 1 | 1 | 99 | 23 | 0.34 |
| 831 | Juan Wei | 5 | 5 | 36 | 4 | 0.34 |
| 832 | Klaus-Günter Kensy | 4 | 4 | 43 | 11 | 0.34 |
| 833 | Na Chen | 4 | 4 | 50 | 9 | 0.33 |
| 834 | Xiulan Yuan | 4 | 4 | 50 | 9 | 0.33 |
| 835 | Franck Hernandez Le Leclerc | 6 | 5 | 19 | 4 | 0.33 |
| 836 | Christopher Johnson | 2 | 2 | 109 | 11 | 0.33 |
| 837 | Fang Meng | 5 | 5 | 35 | 4 | 0.33 |
| 838 | Qiang Pan | 5 | 5 | 35 | 4 | 0.33 |
| 839 | Tao Feng | 5 | 5 | 35 | 4 | 0.33 |
| 840 | Xia Zhou | 5 | 5 | 35 | 4 | 0.33 |
| 841 | Xiulan Cao | 5 | 5 | 35 | 4 | 0.33 |
| 842 | Xiulan Lai | 5 | 5 | 35 | 4 | 0.33 |
| 843 | Guiying Jia | 4 | 4 | 57 | 7 | 0.33 |
| 844 | Juan Gong | 6 | 6 | 16 | 0 | 0.33 |
| 845 | Wei Liu | 6 | 6 | 12 | 1 | 0.33 |
| 846 | Asta Reising | 1 | 1 | 93 | 24 | 0.33 |
| 847 | Karin Metz | 1 | 1 | 93 | 24 | 0.33 |
| 848 | Renegade Harmony | 3 | 3 | 67 | 13 | 0.33 |
| 849 | Claire Holmes | 8 | 5 | 0 | 0 | 0.33 |
| 850 | Meike van Boven | 4 | 4 | 52 | 8 | 0.33 |
| 851 | Na Yi | 6 | 5 | 21 | 3 | 0.33 |
| 852 | Yong Tian | 3 | 3 | 63 | 14 | 0.33 |
| 853 | Fang Tang | 5 | 5 | 37 | 3 | 0.33 |
| 854 | Jing Gao | 3 | 3 | 70 | 12 | 0.33 |
| 855 | Yan Fang | 5 | 5 | 33 | 4 | 0.33 |
| 856 | Lei Ma | 6 | 4 | 30 | 5 | 0.33 |
| 857 | Li Cheng | 5 | 5 | 36 | 3 | 0.33 |
| 858 | Kelli Rodriguez | 3 | 3 | 69 | 12 | 0.33 |
| 859 | Li Jia | 5 | 5 | 32 | 4 | 0.33 |
| 860 | Ping Fan | 5 | 5 | 32 | 4 | 0.33 |
| 861 | Ping Xiong | 2 | 2 | 80 | 18 | 0.33 |
| 862 | Tao Han | 2 | 2 | 80 | 18 | 0.33 |
| 863 | Na Xiao | 4 | 4 | 54 | 7 | 0.33 |
| 864 | Tao Dong | 3 | 3 | 65 | 13 | 0.33 |
| 865 | Guiying Zhong | 5 | 5 | 39 | 2 | 0.33 |
| 866 | Juan Liu | 5 | 5 | 39 | 2 | 0.33 |
| 867 | Na Yin | 5 | 5 | 39 | 2 | 0.33 |
| 868 | Jie Wei | 4 | 4 | 46 | 9 | 0.33 |
| 869 | Iolanda Prada | 5 | 5 | 31 | 4 | 0.33 |
| 870 | Jie Fu | 5 | 5 | 31 | 4 | 0.33 |
| 871 | Na Li | 5 | 5 | 31 | 4 | 0.33 |
| 872 | Wei Xiao | 5 | 5 | 27 | 5 | 0.33 |
| 873 | Min Jiang | 5 | 5 | 38 | 2 | 0.33 |
| 874 | Yan Luo | 5 | 5 | 38 | 2 | 0.33 |
| 875 | Qiang Ren | 3 | 3 | 71 | 11 | 0.33 |
| 876 | Yong Yi | 5 | 5 | 34 | 3 | 0.33 |
| 877 | Guiying Lei | 5 | 5 | 30 | 4 | 0.33 |
| 878 | Xia Kang | 5 | 5 | 37 | 2 | 0.33 |
| 879 | Dunja Reinhardt | 5 | 5 | 22 | 6 | 0.32 |
| 880 | Tao Kang | 4 | 4 | 55 | 6 | 0.32 |
| 881 | Catherine Prévost | 5 | 5 | 18 | 7 | 0.32 |
| 882 | Lilo Cichorius | 5 | 5 | 14 | 8 | 0.32 |
| 883 | Tina Hobbs | 3 | 3 | 62 | 13 | 0.32 |
| 884 | Jun Wei | 5 | 5 | 32 | 3 | 0.32 |
| 885 | Qiang Xu | 5 | 5 | 32 | 3 | 0.32 |
| 886 | Wei Yao | 5 | 5 | 32 | 3 | 0.32 |
| 887 | Xia Qin | 5 | 5 | 32 | 3 | 0.32 |
| 888 | Jing Yang | 3 | 3 | 65 | 12 | 0.32 |
| 889 | Feliciana Figuerola Cruz | 5 | 5 | 28 | 4 | 0.32 |
| 890 | Ming Fang | 3 | 3 | 72 | 10 | 0.32 |
| 891 | Rusty Riggins | 6 | 6 | 9 | 0 | 0.32 |
| 892 | Qiang Zhou | 5 | 5 | 20 | 6 | 0.32 |
| 893 | Tao Guo | 5 | 5 | 31 | 3 | 0.32 |
| 894 | Tao Shen | 5 | 5 | 31 | 3 | 0.32 |
| 895 | Adrien Charles | 5 | 4 | 37 | 6 | 0.32 |
| 896 | Olga Labudda | 4 | 4 | 31 | 12 | 0.32 |
| 897 | Yong Zhu | 5 | 5 | 27 | 4 | 0.32 |
| 898 | Fang Du | 5 | 5 | 34 | 2 | 0.32 |
| 899 | Xiuying Peng | 5 | 5 | 34 | 2 | 0.32 |
| 900 | Janet Wood | 2 | 1 | 99 | 16 | 0.32 |
| 901 | Olivia Morgan | 2 | 1 | 99 | 16 | 0.32 |
| 902 | Ricky Evans | 2 | 1 | 99 | 16 | 0.32 |
| 903 | Theresa Bradley | 2 | 1 | 99 | 16 | 0.32 |
| 904 | The Tide Singer's Knot | 8 | 4 | 6 | 1 | 0.32 |
| 905 | Xiulan Zheng | 5 | 5 | 30 | 3 | 0.32 |
| 906 | Tiffany Gill | 4 | 4 | 30 | 12 | 0.32 |
| 907 | Juan Wen | 5 | 5 | 26 | 4 | 0.32 |
| 908 | Ping Xu | 5 | 5 | 33 | 2 | 0.32 |
| 909 | Gang Yu | 5 | 4 | 39 | 5 | 0.32 |
| 910 | Qiang Fan | 5 | 4 | 39 | 5 | 0.32 |
| 911 | Liquid Vortex | 3 | 3 | 55 | 14 | 0.32 |
| 912 | Yong Tan | 4 | 4 | 40 | 9 | 0.32 |
| 913 | Luis Holt | 2 | 2 | 99 | 11 | 0.32 |
| 914 | Silke Verda | 2 | 2 | 99 | 11 | 0.32 |
| 915 | Michelle Williams | 4 | 4 | 47 | 7 | 0.32 |
| 916 | Min Xie | 4 | 4 | 47 | 7 | 0.32 |
| 917 | Laurie Campbell | 4 | 4 | 17 | 15 | 0.32 |
| 918 | Xavier Leclerc | 5 | 5 | 28 | 3 | 0.32 |
| 919 | Fang Ding | 5 | 4 | 30 | 7 | 0.32 |
| 920 | Li Xia | 5 | 5 | 31 | 2 | 0.32 |
| 921 | Ryan Rodriguez | 4 | 4 | 53 | 5 | 0.31 |
| 922 | Marcia Davis | 5 | 4 | 22 | 9 | 0.31 |
| 923 | Carolyn Schultz | 6 | 5 | 7 | 4 | 0.31 |
| 924 | Lori Hall | 5 | 5 | 12 | 7 | 0.31 |
| 925 | Chao Yan | 5 | 5 | 23 | 4 | 0.31 |
| 926 | Lei Fan | 5 | 5 | 30 | 2 | 0.31 |
| 927 | Brian Gonzalez | 5 | 5 | 26 | 3 | 0.31 |
| 928 | Noah Overeem | 5 | 5 | 26 | 3 | 0.31 |
| 929 | Ryan Austin | 2 | 2 | 74 | 17 | 0.31 |
| 930 | Whispers & Echoes | 4 | 4 | 48 | 6 | 0.31 |
| 931 | Annegrete Röhrdanz | 4 | 3 | 54 | 9 | 0.31 |
| 932 | Juan Long | 5 | 5 | 22 | 4 | 0.31 |
| 933 | Na Yao | 5 | 5 | 22 | 4 | 0.31 |
| 934 | Yang Zheng | 5 | 4 | 39 | 4 | 0.31 |
| 935 | Li Qiu | 2 | 2 | 81 | 15 | 0.31 |
| 936 | Joshua Cruz | 4 | 4 | 44 | 7 | 0.31 |
| 937 | Pulse Collective | 4 | 4 | 44 | 7 | 0.31 |
| 938 | Li Gao | 5 | 5 | 29 | 2 | 0.31 |
| 939 | Min Chen | 5 | 5 | 29 | 2 | 0.31 |
| 940 | Guiying Tao | 5 | 4 | 35 | 5 | 0.31 |
| 941 | The Hollow Monarchs | 7 | 5 | 4 | 0 | 0.31 |
| 942 | Cassian Storm | 8 | 4 | 1 | 1 | 0.31 |
| 943 | Wei Cui | 5 | 5 | 25 | 3 | 0.31 |
| 944 | Yesenia Miller | 1 | 1 | 95 | 20 | 0.31 |
| 945 | Hinrich Weimer | 3 | 3 | 58 | 12 | 0.31 |
| 946 | Jun Xiong | 5 | 5 | 21 | 4 | 0.31 |
| 947 | Ming Xue | 4 | 4 | 43 | 7 | 0.31 |
| 948 | Guiying Yuan | 5 | 5 | 28 | 2 | 0.31 |
| 949 | Angelica Sullivan | 2 | 2 | 98 | 10 | 0.31 |
| 950 | Kay van Dooren-Bastiaense | 2 | 2 | 98 | 10 | 0.31 |
| 951 | Gerhild Mälzer-Albers | 1 | 1 | 83 | 23 | 0.31 |
| 952 | Hannelore Rosemann | 1 | 1 | 83 | 23 | 0.31 |
| 953 | Lei Cui | 4 | 4 | 46 | 6 | 0.31 |
| 954 | Jeanne Guillou | 5 | 5 | 16 | 5 | 0.31 |
| 955 | Sienna Fox | 7 | 5 | 2 | 0 | 0.31 |
| 956 | Min Guo | 4 | 4 | 49 | 5 | 0.31 |
| 957 | Travis Williams | 5 | 4 | 29 | 6 | 0.31 |
| 958 | Jie Deng | 5 | 5 | 30 | 1 | 0.31 |
| 959 | Bernfried Stolze | 4 | 4 | 41 | 7 | 0.31 |
| 960 | Min Xia | 4 | 3 | 58 | 7 | 0.31 |
| 961 | Jason Jordan | 3 | 3 | 52 | 13 | 0.31 |
| 962 | Yang Xu | 2 | 2 | 81 | 14 | 0.31 |
| 963 | Lei Qin | 4 | 4 | 44 | 6 | 0.31 |
| 964 | Yong Sun | 4 | 4 | 44 | 6 | 0.31 |
| 965 | David Lopez | 4 | 4 | 40 | 7 | 0.31 |
| 966 | Joseph Alvarado | 3 | 3 | 62 | 10 | 0.31 |
| 967 | Min Cui | 5 | 5 | 25 | 2 | 0.31 |
| 968 | Ming He | 5 | 5 | 25 | 2 | 0.31 |
| 969 | Yan Yuan | 5 | 5 | 25 | 2 | 0.31 |
| 970 | Willow Sage | 7 | 5 | 0 | 0 | 0.31 |
| 971 | Laura Dillon | 1 | 1 | 80 | 23 | 0.30 |
| 972 | Nicholas Boyd | 1 | 1 | 80 | 23 | 0.30 |
| 973 | Wei Cao | 4 | 4 | 43 | 6 | 0.30 |
| 974 | Gundula Löchel | 3 | 3 | 54 | 12 | 0.30 |
| 975 | Phantom Harmony | 3 | 3 | 54 | 12 | 0.30 |
| 976 | Qiang Du | 5 | 5 | 28 | 1 | 0.30 |
| 977 | Yong Tang | 5 | 5 | 28 | 1 | 0.30 |
| 978 | Shelby Fletcher | 2 | 1 | 82 | 18 | 0.30 |
| 979 | Jun Fu | 4 | 4 | 50 | 4 | 0.30 |
| 980 | Ming Wan | 5 | 5 | 24 | 2 | 0.30 |
| 981 | Wei Huang | 5 | 5 | 24 | 2 | 0.30 |
| 982 | Juan Qiu | 4 | 4 | 46 | 5 | 0.30 |
| 983 | Lei Sun | 5 | 5 | 20 | 3 | 0.30 |
| 984 | Intermezzo Collective | 3 | 3 | 53 | 12 | 0.30 |
| 985 | Min Shen | 5 | 4 | 22 | 7 | 0.30 |
| 986 | Tao Chang | 3 | 3 | 60 | 10 | 0.30 |
| 987 | Fang Wei | 5 | 5 | 23 | 2 | 0.30 |
| 988 | Loretta Roberts | 4 | 4 | 23 | 11 | 0.30 |
| 989 | Ming Cao | 4 | 4 | 45 | 5 | 0.30 |
| 990 | Horst Barkholz | 4 | 4 | 37 | 7 | 0.30 |
| 991 | The Seekers | 4 | 4 | 37 | 7 | 0.30 |
| 992 | Emir Yohannan | 2 | 2 | 37 | 25 | 0.30 |
| 993 | Juan Xue | 5 | 5 | 22 | 2 | 0.30 |
| 994 | Joe Taylor | 4 | 4 | 44 | 5 | 0.30 |
| 995 | Juan Lei | 5 | 5 | 18 | 3 | 0.30 |
| 996 | Yang Long | 4 | 4 | 40 | 6 | 0.30 |
| 997 | Fang Pan | 5 | 5 | 25 | 1 | 0.30 |
| 998 | Li Hu | 5 | 5 | 25 | 1 | 0.30 |
| 999 | Xiuying Jin | 4 | 4 | 36 | 7 | 0.30 |
| 1000 | Qiang Peng | 5 | 4 | 27 | 5 | 0.30 |
| 1001 | Chao Dai | 5 | 5 | 24 | 1 | 0.30 |
| 1002 | Jie Yin | 5 | 4 | 30 | 4 | 0.30 |
| 1003 | Xiuying Gu | 4 | 4 | 46 | 4 | 0.30 |
| 1004 | Anne Miles | 1 | 1 | 94 | 18 | 0.30 |
| 1005 | Martial Harmonies | 5 | 5 | 20 | 2 | 0.30 |
| 1006 | Rebekka Lehmann | 4 | 4 | 31 | 8 | 0.30 |
| 1007 | Jun Cui | 5 | 5 | 23 | 1 | 0.30 |
| 1008 | Li Feng | 4 | 4 | 41 | 5 | 0.29 |
| 1009 | Samuel Gutierrez | 4 | 4 | 41 | 5 | 0.29 |
| 1010 | Guiying Mo | 5 | 5 | 15 | 3 | 0.29 |
| 1011 | Sean Rodgers | 4 | 4 | 37 | 6 | 0.29 |
| 1012 | Hazel Kara | 5 | 5 | 11 | 4 | 0.29 |
| 1013 | Jam & Honey | 5 | 5 | 11 | 4 | 0.29 |
| 1014 | Midnight Recursion | 5 | 5 | 18 | 2 | 0.29 |
| 1015 | Kenneth Fox | 2 | 2 | 62 | 17 | 0.29 |
| 1016 | Yang Xiang | 3 | 3 | 47 | 12 | 0.29 |
| 1017 | Artur Nurkiewicz | 5 | 5 | 6 | 5 | 0.29 |
| 1018 | Roberto Pausini | 4 | 4 | 17 | 11 | 0.29 |
| 1019 | Xiulan Yang | 3 | 3 | 61 | 8 | 0.29 |
| 1020 | Guiying Peng | 4 | 4 | 35 | 6 | 0.29 |
| 1021 | Jing Meng | 4 | 4 | 35 | 6 | 0.29 |
| 1022 | Xiuying Hou | 4 | 4 | 35 | 6 | 0.29 |
| 1023 | Xiuying Cui | 3 | 3 | 46 | 12 | 0.29 |
| 1024 | Fang Liu | 4 | 4 | 42 | 4 | 0.29 |
| 1025 | Marek Oleksa | 5 | 5 | 5 | 5 | 0.29 |
| 1026 | Cyprian Ziniewicz | 5 | 4 | 11 | 8 | 0.29 |
| 1027 | Konrad Goss | 4 | 4 | 12 | 12 | 0.29 |
| 1028 | Kornel Preś | 4 | 4 | 12 | 12 | 0.29 |
| 1029 | Wei Meng | 5 | 5 | 23 | 0 | 0.29 |
| 1030 | Ming Fan | 4 | 4 | 34 | 6 | 0.29 |
| 1031 | Ming Qiu | 4 | 4 | 34 | 6 | 0.29 |
| 1032 | Xiuying Du | 4 | 3 | 51 | 6 | 0.29 |
| 1033 | Leslie Barnes | 3 | 3 | 56 | 9 | 0.29 |
| 1034 | Teresa Williams | 3 | 3 | 56 | 9 | 0.29 |
| 1035 | Yong Gong | 3 | 3 | 56 | 9 | 0.29 |
| 1036 | Wei Ma | 2 | 2 | 74 | 13 | 0.29 |
| 1037 | Wei Hu | 4 | 4 | 37 | 5 | 0.29 |
| 1038 | Xiulan Fu | 4 | 4 | 37 | 5 | 0.29 |
| 1039 | Yan Gao | 4 | 3 | 54 | 5 | 0.29 |
| 1040 | Asuka Takahashi | 5 | 5 | 11 | 3 | 0.29 |
| 1041 | Qiang Luo | 5 | 4 | 28 | 3 | 0.29 |
| 1042 | Qiang Qiao | 4 | 4 | 33 | 6 | 0.29 |
| 1043 | Michelle Vallenduuk | 5 | 5 | 7 | 4 | 0.29 |
| 1044 | Fang Ren | 5 | 5 | 18 | 1 | 0.29 |
| 1045 | Yang Mo | 5 | 5 | 18 | 1 | 0.29 |
| 1046 | Guiying Chen | 3 | 3 | 51 | 10 | 0.29 |
| 1047 | Xiulan Jiang | 5 | 5 | 14 | 2 | 0.29 |
| 1048 | Erkan Barkholz | 5 | 4 | 20 | 5 | 0.29 |
| 1049 | Xia Lu | 3 | 3 | 62 | 7 | 0.29 |
| 1050 | The Brine Choir | 7 | 4 | 6 | 0 | 0.29 |
| 1051 | Chao Ding | 4 | 4 | 36 | 5 | 0.29 |
| 1052 | Insurgencia | 3 | 3 | 32 | 15 | 0.29 |
| 1053 | Jörg Niemeier | 5 | 5 | 17 | 1 | 0.29 |
| 1054 | Yan Xia | 2 | 1 | 56 | 22 | 0.29 |
| 1055 | Ping Ren | 3 | 3 | 61 | 7 | 0.28 |
| 1056 | Xiuying Zhong | 4 | 4 | 24 | 8 | 0.28 |
| 1057 | Ping Zhang | 4 | 4 | 35 | 5 | 0.28 |
| 1058 | Scott Johnson | 4 | 4 | 35 | 5 | 0.28 |
| 1059 | Laura Clark | 5 | 5 | 9 | 3 | 0.28 |
| 1060 | Li Mo | 5 | 4 | 26 | 3 | 0.28 |
| 1061 | Na Xu | 3 | 3 | 53 | 9 | 0.28 |
| 1062 | Ming Dai | 5 | 5 | 16 | 1 | 0.28 |
| 1063 | Min Ding | 4 | 3 | 44 | 7 | 0.28 |
| 1064 | Min Zhou | 4 | 4 | 34 | 5 | 0.28 |
| 1065 | Na Xie | 4 | 4 | 34 | 5 | 0.28 |
| 1066 | Narrow Passages | 4 | 4 | 34 | 5 | 0.28 |
| 1067 | Fang Gao | 5 | 5 | 19 | 0 | 0.28 |
| 1068 | Ping Tang | 3 | 3 | 52 | 9 | 0.28 |
| 1069 | Yan Wang | 5 | 5 | 15 | 1 | 0.28 |
| 1070 | Ante Wagenknecht | 2 | 2 | 74 | 12 | 0.28 |
| 1071 | Mariah Ramirez | 4 | 4 | 37 | 4 | 0.28 |
| 1072 | Yong Deng | 5 | 5 | 11 | 2 | 0.28 |
| 1073 | Ping Hou | 3 | 3 | 59 | 7 | 0.28 |
| 1074 | Silver Veil | 8 | 3 | 4 | 0 | 0.28 |
| 1075 | Tina Raymond | 3 | 3 | 55 | 8 | 0.28 |
| 1076 | Li Ren | 4 | 4 | 40 | 3 | 0.28 |
| 1077 | Jennifer Diaz | 3 | 3 | 51 | 9 | 0.28 |
| 1078 | Stefan Berus | 5 | 5 | 10 | 2 | 0.28 |
| 1079 | Cassette Future | 7 | 4 | 2 | 0 | 0.28 |
| 1080 | Brian Hughes | 5 | 5 | 6 | 3 | 0.28 |
| 1081 | Jun Zheng | 5 | 5 | 17 | 0 | 0.28 |
| 1082 | Yang Cheng | 5 | 5 | 17 | 0 | 0.28 |
| 1083 | Wei Ye | 5 | 5 | 13 | 1 | 0.28 |
| 1084 | Jeffrey Munoz PhD | 2 | 2 | 61 | 15 | 0.28 |
| 1085 | Thomas Salinas | 2 | 2 | 61 | 15 | 0.28 |
| 1086 | James Taylor | 5 | 5 | 9 | 2 | 0.28 |
| 1087 | Xia Guo | 3 | 3 | 57 | 7 | 0.28 |
| 1088 | Xia Hu | 5 | 4 | 26 | 2 | 0.28 |
| 1089 | Erin Fox | 4 | 4 | 31 | 5 | 0.28 |
| 1090 | Jun Tan | 4 | 4 | 31 | 5 | 0.28 |
| 1091 | Wei He | 4 | 4 | 31 | 5 | 0.28 |
| 1092 | Michaela Kelley | 5 | 4 | 11 | 6 | 0.28 |
| 1093 | Miguel Johnston | 5 | 4 | 11 | 6 | 0.28 |
| 1094 | Jie Kang | 5 | 5 | 16 | 0 | 0.28 |
| 1095 | Amy Lee | 4 | 4 | 27 | 6 | 0.28 |
| 1096 | Samuel Robertson | 4 | 4 | 27 | 6 | 0.28 |
| 1097 | Juan Xiang | 4 | 3 | 44 | 6 | 0.28 |
| 1098 | Yong Zhang | 5 | 4 | 29 | 1 | 0.28 |
| 1099 | Nela Melcer | 4 | 4 | 8 | 11 | 0.28 |
| 1100 | Yong Mao | 4 | 4 | 30 | 5 | 0.28 |
| 1101 | John Garcia | 3 | 3 | 41 | 11 | 0.28 |
| 1102 | Matthew Cowan | 3 | 3 | 41 | 11 | 0.28 |
| 1103 | Rusty Anvil | 3 | 3 | 41 | 11 | 0.28 |
| 1104 | Jie Tan | 3 | 2 | 58 | 11 | 0.28 |
| 1105 | Sophie Ramirez | 5 | 5 | 15 | 0 | 0.28 |
| 1106 | Xiulan Tang | 5 | 5 | 15 | 0 | 0.28 |
| 1107 | Jun Gong | 5 | 4 | 28 | 1 | 0.28 |
| 1108 | Wei Zhang | 4 | 4 | 33 | 4 | 0.28 |
| 1109 | Xiulan Duan | 4 | 4 | 33 | 4 | 0.28 |
| 1110 | Aleksander Przybyś | 5 | 5 | 7 | 2 | 0.28 |
| 1111 | Fang Tan | 5 | 5 | 7 | 2 | 0.28 |
| 1112 | Abdullah Bauer | 1 | 1 | 99 | 13 | 0.27 |
| 1113 | Barbara Haas | 1 | 1 | 99 | 13 | 0.27 |
| 1114 | Birgid Junck-Sauer | 1 | 1 | 99 | 13 | 0.27 |
| 1115 | Brandi Tran | 1 | 1 | 99 | 13 | 0.27 |
| 1116 | Brenda Hammond | 1 | 1 | 99 | 13 | 0.27 |
| 1117 | David Clements | 1 | 1 | 99 | 13 | 0.27 |
| 1118 | David Patel | 1 | 1 | 99 | 13 | 0.27 |
| 1119 | Gabriel Ruppert | 1 | 1 | 99 | 13 | 0.27 |
| 1120 | Hans-Christian Drub | 1 | 1 | 99 | 13 | 0.27 |
| 1121 | Keith Navarro | 1 | 1 | 99 | 13 | 0.27 |
| 1122 | Susan Haney | 1 | 1 | 99 | 13 | 0.27 |
| 1123 | Carolyn Hall | 4 | 4 | 21 | 7 | 0.27 |
| 1124 | Rachel Stein | 2 | 2 | 69 | 12 | 0.27 |
| 1125 | Fang Feng | 4 | 4 | 32 | 4 | 0.27 |
| 1126 | Li Zhou | 4 | 4 | 32 | 4 | 0.27 |
| 1127 | Matthew Yoder | 4 | 3 | 23 | 11 | 0.27 |
| 1128 | Na Ye | 4 | 4 | 28 | 5 | 0.27 |
| 1129 | Yan Qian | 2 | 2 | 39 | 20 | 0.27 |
| 1130 | Dariusz Olszowa | 5 | 5 | 2 | 3 | 0.27 |
| 1131 | Verdant Pulse | 4 | 3 | 30 | 9 | 0.27 |
| 1132 | Maciej Siejak | 5 | 4 | 4 | 7 | 0.27 |
| 1133 | Fang Hou | 4 | 4 | 31 | 4 | 0.27 |
| 1134 | Yang Xiao | 4 | 4 | 31 | 4 | 0.27 |
| 1135 | Maya Jensen | 5 | 5 | 12 | 0 | 0.27 |
| 1136 | Fang Gu | 4 | 4 | 34 | 3 | 0.27 |
| 1137 | Na Song | 4 | 4 | 34 | 3 | 0.27 |
| 1138 | Christine Ward | 3 | 3 | 45 | 9 | 0.27 |
| 1139 | Lisa Hofmann | 3 | 3 | 45 | 9 | 0.27 |
| 1140 | Sonora Flux | 3 | 3 | 45 | 9 | 0.27 |
| 1141 | Lei Cheng | 2 | 2 | 67 | 12 | 0.27 |
| 1142 | Guiying Tang | 4 | 4 | 30 | 4 | 0.27 |
| 1143 | Yong Yu | 4 | 4 | 30 | 4 | 0.27 |
| 1144 | Jie Jia | 5 | 4 | 21 | 2 | 0.27 |
| 1145 | Ping Gong | 4 | 4 | 37 | 2 | 0.27 |
| 1146 | Gregory Williams | 3 | 3 | 48 | 8 | 0.27 |
| 1147 | Fang Jia | 4 | 4 | 33 | 3 | 0.27 |
| 1148 | Tao Jiang | 4 | 4 | 33 | 3 | 0.27 |
| 1149 | Scott Sanders | 3 | 3 | 44 | 9 | 0.27 |
| 1150 | Jun Qiu | 2 | 2 | 66 | 12 | 0.27 |
| 1151 | Malwina Penar | 4 | 4 | 29 | 4 | 0.27 |
| 1152 | Michael Harris | 4 | 4 | 29 | 4 | 0.27 |
| 1153 | Xia Yu | 3 | 3 | 51 | 7 | 0.27 |
| 1154 | Xia Jin | 4 | 3 | 42 | 5 | 0.27 |
| 1155 | Wei Tian | 4 | 4 | 32 | 3 | 0.27 |
| 1156 | Heino Ladeck | 4 | 4 | 17 | 7 | 0.27 |
| 1157 | Xia Qiu | 4 | 4 | 28 | 4 | 0.27 |
| 1158 | Qiang Meng | 4 | 3 | 34 | 7 | 0.27 |
| 1159 | Anthony Gutierrez | 2 | 2 | 61 | 13 | 0.27 |
| 1160 | Alfred Thibault | 3 | 3 | 35 | 11 | 0.27 |
| 1161 | Synaptic Stream | 3 | 3 | 35 | 11 | 0.27 |
| 1162 | Zoé-Agnès Delaunay | 3 | 3 | 35 | 11 | 0.27 |
| 1163 | Finn McGraw | 5 | 5 | 9 | 0 | 0.27 |
| 1164 | William Tidewell | 5 | 5 | 9 | 0 | 0.27 |
| 1165 | Chao Yuan | 4 | 4 | 31 | 3 | 0.27 |
| 1166 | Jun Su | 4 | 4 | 31 | 3 | 0.27 |
| 1167 | Ping Du | 4 | 4 | 31 | 3 | 0.27 |
| 1168 | Juan Zhu | 4 | 4 | 27 | 4 | 0.27 |
| 1169 | Xia Song | 4 | 4 | 27 | 4 | 0.27 |
| 1170 | Elizabeth Saunders | 4 | 4 | 23 | 5 | 0.26 |
| 1171 | Jing Liao | 4 | 4 | 30 | 3 | 0.26 |
| 1172 | Juan Tan | 4 | 4 | 30 | 3 | 0.26 |
| 1173 | Na Zhu | 4 | 4 | 30 | 3 | 0.26 |
| 1174 | Tao Mo | 4 | 4 | 30 | 3 | 0.26 |
| 1175 | Xia Yao | 4 | 4 | 30 | 3 | 0.26 |
| 1176 | Yan Li | 4 | 4 | 30 | 3 | 0.26 |
| 1177 | Marcel Derek | 3 | 3 | 41 | 9 | 0.26 |
| 1178 | Wei Yu | 3 | 3 | 41 | 9 | 0.26 |
| 1179 | Ming Xiao | 5 | 4 | 21 | 1 | 0.26 |
| 1180 | Xiuying Guo | 4 | 4 | 26 | 4 | 0.26 |
| 1181 | Final Order | 4 | 4 | 22 | 5 | 0.26 |
| 1182 | Tao Huang | 4 | 4 | 33 | 2 | 0.26 |
| 1183 | Wei Tan | 4 | 4 | 33 | 2 | 0.26 |
| 1184 | Wei Dai | 4 | 3 | 39 | 5 | 0.26 |
| 1185 | Juan Lai | 5 | 4 | 24 | 0 | 0.26 |
| 1186 | Lei Jia | 4 | 4 | 29 | 3 | 0.26 |
| 1187 | Min Yao | 4 | 4 | 29 | 3 | 0.26 |
| 1188 | Na Liao | 4 | 4 | 29 | 3 | 0.26 |
| 1189 | Walter White | 4 | 4 | 29 | 3 | 0.26 |
| 1190 | Xiulan Deng | 5 | 4 | 20 | 1 | 0.26 |
| 1191 | Xiuying Lin | 5 | 4 | 20 | 1 | 0.26 |
| 1192 | Jennifer Gibson | 2 | 2 | 62 | 12 | 0.26 |
| 1193 | Laura Brown | 2 | 2 | 62 | 12 | 0.26 |
| 1194 | Gordon Cox | 4 | 4 | 25 | 4 | 0.26 |
| 1195 | Fang Qian | 4 | 4 | 32 | 2 | 0.26 |
| 1196 | Coralia Bellweather | 5 | 5 | 6 | 0 | 0.26 |
| 1197 | Lei Pan | 4 | 4 | 28 | 3 | 0.26 |
| 1198 | Craig Cameron | 4 | 4 | 24 | 4 | 0.26 |
| 1199 | Jun Wen | 4 | 4 | 35 | 1 | 0.26 |
| 1200 | Eugene Henderson | 3 | 3 | 46 | 7 | 0.26 |
| 1201 | Psycho Twang | 3 | 3 | 46 | 7 | 0.26 |
| 1202 | David Hayes | 4 | 4 | 20 | 5 | 0.26 |
| 1203 | Luciana Iacovelli | 1 | 1 | 68 | 19 | 0.26 |
| 1204 | Fang Zheng | 4 | 4 | 31 | 2 | 0.26 |
| 1205 | Wei Peng | 4 | 3 | 37 | 5 | 0.26 |
| 1206 | Kendra Rivera | 3 | 3 | 42 | 8 | 0.26 |
| 1207 | Joker's Smile | 4 | 4 | 16 | 6 | 0.26 |
| 1208 | Renee Williams | 4 | 4 | 16 | 6 | 0.26 |
| 1209 | Echoes of Arcadia | 4 | 4 | 27 | 3 | 0.26 |
| 1210 | Ming Li | 4 | 4 | 27 | 3 | 0.26 |
| 1211 | Yan Chen | 3 | 3 | 38 | 9 | 0.26 |
| 1212 | Jie Wan | 4 | 4 | 23 | 4 | 0.26 |
| 1213 | Neon Horizon | 4 | 4 | 23 | 4 | 0.26 |
| 1214 | Xiulan Cai | 4 | 4 | 23 | 4 | 0.26 |
| 1215 | Ming Xu | 3 | 3 | 45 | 7 | 0.26 |
| 1216 | Na Hu | 3 | 3 | 45 | 7 | 0.26 |
| 1217 | Ping Cui | 3 | 3 | 45 | 7 | 0.26 |
| 1218 | Lisa Lopez | 2 | 2 | 67 | 10 | 0.26 |
| 1219 | Xia Fang | 4 | 4 | 30 | 2 | 0.26 |
| 1220 | Yang Yang | 4 | 4 | 30 | 2 | 0.26 |
| 1221 | Chao Jiang | 4 | 3 | 36 | 5 | 0.26 |
| 1222 | Ronald Kennedy | 3 | 3 | 41 | 8 | 0.26 |
| 1223 | Ewan MacCrae | 5 | 5 | 4 | 0 | 0.26 |
| 1224 | Freya Lindholm | 5 | 5 | 4 | 0 | 0.26 |
| 1225 | Jun Du | 4 | 4 | 26 | 3 | 0.26 |
| 1226 | Ming Hu | 4 | 3 | 43 | 3 | 0.26 |
| 1227 | Cordula Ehlert | 2 | 2 | 59 | 12 | 0.26 |
| 1228 | Xia Tan | 4 | 4 | 33 | 1 | 0.26 |
| 1229 | Michael Holloway | 3 | 3 | 44 | 7 | 0.26 |
| 1230 | Fiona Mercer | 5 | 5 | 3 | 0 | 0.26 |
| 1231 | Liam O'Sullivan | 5 | 5 | 3 | 0 | 0.26 |
| 1232 | Ping Deng | 4 | 4 | 25 | 3 | 0.26 |
| 1233 | Xiulan Kang | 4 | 4 | 25 | 3 | 0.26 |
| 1234 | Anouk Schatteleijn | 3 | 3 | 36 | 9 | 0.26 |
| 1235 | Li Wu | 4 | 4 | 17 | 5 | 0.25 |
| 1236 | Dawn Gross | 2 | 2 | 65 | 10 | 0.25 |
| 1237 | John Gray | 2 | 2 | 65 | 10 | 0.25 |
| 1238 | Gang Hao | 4 | 4 | 28 | 2 | 0.25 |
| 1239 | Guiying Jiang | 4 | 4 | 28 | 2 | 0.25 |
| 1240 | Jing Song | 4 | 3 | 34 | 5 | 0.25 |
| 1241 | Guiying Hao | 3 | 3 | 50 | 5 | 0.25 |
| 1242 | Alexis Ruiz | 1 | 1 | 98 | 10 | 0.25 |
| 1243 | Brian Ballard | 1 | 1 | 98 | 10 | 0.25 |
| 1244 | Candice Santiago | 1 | 1 | 98 | 10 | 0.25 |
| 1245 | David Bates Jr. | 1 | 1 | 98 | 10 | 0.25 |
| 1246 | Eric Shelton | 1 | 1 | 98 | 10 | 0.25 |
| 1247 | George Williams | 1 | 1 | 98 | 10 | 0.25 |
| 1248 | Jared Newman | 1 | 1 | 98 | 10 | 0.25 |
| 1249 | Jodi Miller | 1 | 1 | 98 | 10 | 0.25 |
| 1250 | Jonathan Butler | 1 | 1 | 98 | 10 | 0.25 |
| 1251 | Joris Heerschop-Weylant | 1 | 1 | 98 | 10 | 0.25 |
| 1252 | Laura Christian | 1 | 1 | 98 | 10 | 0.25 |
| 1253 | Lauren Mccoy | 1 | 1 | 98 | 10 | 0.25 |
| 1254 | Paige Case | 1 | 1 | 98 | 10 | 0.25 |
| 1255 | Richard Mendoza | 1 | 1 | 98 | 10 | 0.25 |
| 1256 | Robert Lee | 1 | 1 | 98 | 10 | 0.25 |
| 1257 | Robert Washington | 1 | 1 | 98 | 10 | 0.25 |
| 1258 | Roger Porter | 1 | 1 | 98 | 10 | 0.25 |
| 1259 | Shelby Dixon | 1 | 1 | 98 | 10 | 0.25 |
| 1260 | Tanya Pittman | 1 | 1 | 98 | 10 | 0.25 |
| 1261 | Thomas Miller | 1 | 1 | 98 | 10 | 0.25 |
| 1262 | Tony Olson | 1 | 1 | 98 | 10 | 0.25 |
| 1263 | Virginia Warner | 1 | 1 | 98 | 10 | 0.25 |
| 1264 | Chao Xie | 2 | 2 | 57 | 12 | 0.25 |
| 1265 | Ping Tao | 4 | 4 | 20 | 4 | 0.25 |
| 1266 | Karin Dippel | 4 | 4 | 16 | 5 | 0.25 |
| 1267 | Guiying Jin | 4 | 4 | 27 | 2 | 0.25 |
| 1268 | Michael Moore | 4 | 4 | 27 | 2 | 0.25 |
| 1269 | Guiying Lin | 3 | 3 | 38 | 8 | 0.25 |
| 1270 | Jun Yan | 4 | 4 | 23 | 3 | 0.25 |
| 1271 | Lei Lai | 4 | 4 | 23 | 3 | 0.25 |
| 1272 | Wei Lu | 4 | 4 | 23 | 3 | 0.25 |
| 1273 | Dierk Bohlander | 3 | 3 | 23 | 12 | 0.25 |
| 1274 | Li Sun | 3 | 2 | 51 | 9 | 0.25 |
| 1275 | Na Yan | 3 | 3 | 41 | 7 | 0.25 |
| 1276 | Lei Zeng | 3 | 2 | 47 | 10 | 0.25 |
| 1277 | Christine Lam | 4 | 4 | 15 | 5 | 0.25 |
| 1278 | Jing Duan | 4 | 4 | 26 | 2 | 0.25 |
| 1279 | Jing Lei | 4 | 4 | 26 | 2 | 0.25 |
| 1280 | Christian Mcpherson | 4 | 4 | 11 | 6 | 0.25 |
| 1281 | Lei Yao | 4 | 4 | 22 | 3 | 0.25 |
| 1282 | Ping Shao | 4 | 4 | 22 | 3 | 0.25 |
| 1283 | Jie Yao | 4 | 3 | 39 | 3 | 0.25 |
| 1284 | Ryan Ford | 4 | 4 | 7 | 7 | 0.25 |
| 1285 | Hilmar Hänel | 4 | 3 | 24 | 7 | 0.25 |
| 1286 | Qiang Liu | 3 | 3 | 40 | 7 | 0.25 |
| 1287 | Gang Xie | 4 | 4 | 25 | 2 | 0.25 |
| 1288 | Lei Cai | 4 | 4 | 25 | 2 | 0.25 |
| 1289 | Wei Pan | 4 | 4 | 25 | 2 | 0.25 |
| 1290 | Na Chang | 4 | 4 | 21 | 3 | 0.25 |
| 1291 | Yang Han | 4 | 4 | 21 | 3 | 0.25 |
| 1292 | Jing Shi | 4 | 4 | 28 | 1 | 0.25 |
| 1293 | Jun Huang | 4 | 4 | 28 | 1 | 0.25 |
| 1294 | Yong Liao | 3 | 3 | 39 | 7 | 0.25 |
| 1295 | Jie Feng | 4 | 4 | 24 | 2 | 0.25 |
| 1296 | Jing Zhu | 4 | 4 | 24 | 2 | 0.25 |
| 1297 | Jun Xiang | 4 | 4 | 24 | 2 | 0.25 |
| 1298 | Shawn Fox | 4 | 4 | 24 | 2 | 0.25 |
| 1299 | Tao Yuan | 4 | 4 | 24 | 2 | 0.25 |
| 1300 | Wei Liang | 4 | 4 | 24 | 2 | 0.25 |
| 1301 | Xia Bai | 4 | 4 | 24 | 2 | 0.25 |
| 1302 | Guiying Zhang | 3 | 3 | 35 | 8 | 0.25 |
| 1303 | Holly Gonzalez | 4 | 4 | 9 | 6 | 0.25 |
| 1304 | Sovereign Elect | 4 | 4 | 9 | 6 | 0.25 |
| 1305 | Fang Yi | 4 | 4 | 20 | 3 | 0.25 |
| 1306 | Juan Cai | 4 | 4 | 20 | 3 | 0.25 |
| 1307 | Jun Cai | 4 | 4 | 20 | 3 | 0.25 |
| 1308 | Xia Wan | 3 | 3 | 42 | 6 | 0.25 |
| 1309 | Collettivo Moderno | 2 | 2 | 53 | 12 | 0.25 |
| 1310 | Lori Lee | 4 | 4 | 16 | 4 | 0.25 |
| 1311 | Li Kong | 4 | 4 | 27 | 1 | 0.25 |
| 1312 | Na Wu | 4 | 3 | 33 | 4 | 0.25 |
| 1313 | Jie Ma | 3 | 3 | 49 | 4 | 0.25 |
| 1314 | Wei Lin | 4 | 4 | 23 | 2 | 0.25 |
| 1315 | Guiying Fu | 4 | 3 | 29 | 5 | 0.25 |
| 1316 | Lisa Smith | 3 | 3 | 23 | 11 | 0.25 |
| 1317 | Matthew Moss | 3 | 3 | 34 | 8 | 0.25 |
| 1318 | Dhanuk Hari | 4 | 4 | 8 | 6 | 0.25 |
| 1319 | Hansh Sidhu | 4 | 4 | 8 | 6 | 0.25 |
| 1320 | Jie Tian | 4 | 4 | 19 | 3 | 0.25 |
| 1321 | Li Zhong | 4 | 4 | 19 | 3 | 0.25 |
| 1322 | Xiulan Tan | 3 | 3 | 41 | 6 | 0.25 |
| 1323 | Xia Wang | 4 | 3 | 32 | 4 | 0.24 |
| 1324 | Fang Qiao | 3 | 3 | 48 | 4 | 0.24 |
| 1325 | Ming Shen | 4 | 4 | 22 | 2 | 0.24 |
| 1326 | Li Tian | 3 | 3 | 33 | 8 | 0.24 |
| 1327 | Fang Dong | 4 | 4 | 18 | 3 | 0.24 |
| 1328 | Yumiko Ito | 4 | 4 | 18 | 3 | 0.24 |
| 1329 | Giuliana Costanzi | 4 | 4 | 14 | 4 | 0.24 |
| 1330 | Maura Chiappetta | 4 | 4 | 14 | 4 | 0.24 |
| 1331 | Chao Qian | 4 | 4 | 25 | 1 | 0.24 |
| 1332 | Silvia Sölzer-van der Dussen | 3 | 3 | 25 | 10 | 0.24 |
| 1333 | Chao Jin | 4 | 4 | 21 | 2 | 0.24 |
| 1334 | Dominic Phillips | 4 | 4 | 21 | 2 | 0.24 |
| 1335 | Jie Wang | 4 | 4 | 21 | 2 | 0.24 |
| 1336 | Li Tan | 4 | 4 | 21 | 2 | 0.24 |
| 1337 | Li Yi | 4 | 4 | 21 | 2 | 0.24 |
| 1338 | Min Wu | 4 | 4 | 21 | 2 | 0.24 |
| 1339 | Yan Xiao | 4 | 4 | 21 | 2 | 0.24 |
| 1340 | Karen Anderson | 4 | 3 | 38 | 2 | 0.24 |
| 1341 | Jie Lei | 3 | 3 | 39 | 6 | 0.24 |
| 1342 | Fang Xiao | 4 | 4 | 24 | 1 | 0.24 |
| 1343 | Tao Yu | 4 | 4 | 24 | 1 | 0.24 |
| 1344 | Greta Löchel-Neureuther | 3 | 3 | 35 | 7 | 0.24 |
| 1345 | Silvana Radisch | 3 | 3 | 35 | 7 | 0.24 |
| 1346 | Xiuying Cao | 3 | 3 | 35 | 7 | 0.24 |
| 1347 | Jing Zhou | 4 | 4 | 20 | 2 | 0.24 |
| 1348 | Ming Luo | 4 | 4 | 20 | 2 | 0.24 |
| 1349 | Xiulan Ma | 4 | 4 | 20 | 2 | 0.24 |
| 1350 | Jillian Salazar | 2 | 2 | 49 | 12 | 0.24 |
| 1351 | Jie Dong | 4 | 4 | 23 | 1 | 0.24 |
| 1352 | Yan Yang | 4 | 4 | 23 | 1 | 0.24 |
| 1353 | John Rogers | 4 | 3 | 29 | 4 | 0.24 |
| 1354 | Xiulan Zhou | 4 | 3 | 29 | 4 | 0.24 |
| 1355 | Midnight Harvest | 3 | 3 | 34 | 7 | 0.24 |
| 1356 | Denise Schroeder | 4 | 4 | 8 | 5 | 0.24 |
| 1357 | Sydney Adams | 4 | 4 | 8 | 5 | 0.24 |
| 1358 | Antonietta Ceravolo-Condoleo | 4 | 4 | 19 | 2 | 0.24 |
| 1359 | Fang Shen | 4 | 4 | 19 | 2 | 0.24 |
| 1360 | Jing Feng | 4 | 4 | 19 | 2 | 0.24 |
| 1361 | Razor's Lament | 4 | 4 | 19 | 2 | 0.24 |
| 1362 | Lei Fang | 3 | 2 | 47 | 8 | 0.24 |
| 1363 | Yang Luo | 4 | 4 | 15 | 3 | 0.24 |
| 1364 | Astrid Lecoq | 4 | 4 | 11 | 4 | 0.24 |
| 1365 | Kläre Schacht-Mielcarek | 4 | 4 | 11 | 4 | 0.24 |
| 1366 | Élodie Albert | 4 | 4 | 11 | 4 | 0.24 |
| 1367 | Li Wen | 4 | 4 | 22 | 1 | 0.24 |
| 1368 | Tao He | 4 | 4 | 22 | 1 | 0.24 |
| 1369 | James Reyes | 3 | 3 | 44 | 4 | 0.24 |
| 1370 | Brandon Vasquez | 4 | 4 | 7 | 5 | 0.24 |
| 1371 | Hex Collective | 4 | 4 | 18 | 2 | 0.24 |
| 1372 | Jing Ding | 4 | 4 | 18 | 2 | 0.24 |
| 1373 | Juan Yan | 4 | 4 | 18 | 2 | 0.24 |
| 1374 | Jun Wang | 4 | 4 | 18 | 2 | 0.24 |
| 1375 | David Miles | 3 | 3 | 29 | 8 | 0.24 |
| 1376 | Domenico Gasperi | 3 | 3 | 40 | 5 | 0.24 |
| 1377 | Jie Du | 3 | 3 | 40 | 5 | 0.24 |
| 1378 | Jie Wu | 3 | 3 | 40 | 5 | 0.24 |
| 1379 | Rozalia Ciepluch | 1 | 1 | 40 | 23 | 0.24 |
| 1380 | Jeffrey Phillips | 4 | 4 | 14 | 3 | 0.24 |
| 1381 | Lei Gao | 4 | 4 | 14 | 3 | 0.24 |
| 1382 | Marcus Douglas | 1 | 1 | 62 | 17 | 0.24 |
| 1383 | Thomas Massey | 1 | 1 | 62 | 17 | 0.24 |
| 1384 | Min Zou | 4 | 3 | 31 | 3 | 0.24 |
| 1385 | Wei Zeng | 4 | 2 | 37 | 6 | 0.24 |
| 1386 | Snout Noise | 3 | 3 | 36 | 6 | 0.24 |
| 1387 | Mathew Chapman III | 3 | 2 | 42 | 9 | 0.24 |
| 1388 | Guiying Su | 4 | 4 | 21 | 1 | 0.24 |
| 1389 | Jie Gu | 4 | 4 | 21 | 1 | 0.24 |
| 1390 | Li Fan | 4 | 4 | 21 | 1 | 0.24 |
| 1391 | Wei Dong | 4 | 4 | 21 | 1 | 0.24 |
| 1392 | Wei Wu | 4 | 4 | 21 | 1 | 0.24 |
| 1393 | Allison Sanford | 1 | 1 | 54 | 19 | 0.24 |
| 1394 | Cindy Smith | 1 | 1 | 54 | 19 | 0.24 |
| 1395 | Szymon Piguła | 1 | 1 | 54 | 19 | 0.24 |
| 1396 | Yan Guo | 4 | 4 | 17 | 2 | 0.24 |
| 1397 | Yong Qian | 4 | 4 | 17 | 2 | 0.24 |
| 1398 | Encrucijada | 4 | 4 | 13 | 3 | 0.24 |
| 1399 | Michelangelo Berlusconi | 4 | 4 | 13 | 3 | 0.24 |
| 1400 | Bogdan Gehringer | 3 | 3 | 35 | 6 | 0.24 |
| 1401 | Juan Tao | 3 | 3 | 35 | 6 | 0.24 |
| 1402 | Li Shen | 3 | 3 | 35 | 6 | 0.24 |
| 1403 | Ming Gu | 3 | 3 | 35 | 6 | 0.24 |
| 1404 | Ming Zhu | 3 | 3 | 35 | 6 | 0.24 |
| 1405 | Wendy Brown | 3 | 3 | 35 | 6 | 0.24 |
| 1406 | Xiuying Tian | 4 | 4 | 20 | 1 | 0.23 |
| 1407 | Tao Tang | 4 | 3 | 22 | 5 | 0.23 |
| 1408 | Chloë de Gruil | 4 | 4 | 12 | 3 | 0.23 |
| 1409 | Frau Adelgunde Hermighausen | 4 | 4 | 12 | 3 | 0.23 |
| 1410 | Ottmar Grein Groth-Butte | 4 | 4 | 12 | 3 | 0.23 |
| 1411 | Qiang Mo | 4 | 3 | 29 | 3 | 0.23 |
| 1412 | Ascendant | 4 | 4 | 8 | 4 | 0.23 |
| 1413 | Maria Freeman | 4 | 4 | 8 | 4 | 0.23 |
| 1414 | Philip Conley | 2 | 2 | 56 | 9 | 0.23 |
| 1415 | Fang Ma | 4 | 4 | 19 | 1 | 0.23 |
| 1416 | Juan Meng | 4 | 4 | 19 | 1 | 0.23 |
| 1417 | Lei Jiang | 4 | 4 | 19 | 1 | 0.23 |
| 1418 | Na Kang | 4 | 4 | 19 | 1 | 0.23 |
| 1419 | Yang Ma | 4 | 4 | 19 | 1 | 0.23 |
| 1420 | Yong Hu | 4 | 4 | 19 | 1 | 0.23 |
| 1421 | Kathleen Davis | 3 | 3 | 19 | 10 | 0.23 |
| 1422 | Jing Yin | 4 | 4 | 15 | 2 | 0.23 |
| 1423 | Li Shao | 4 | 4 | 15 | 2 | 0.23 |
| 1424 | Daniel Roberts | 2 | 2 | 48 | 11 | 0.23 |
| 1425 | Jessica Stafford | 2 | 2 | 48 | 11 | 0.23 |
| 1426 | Margaret Sanchez | 2 | 2 | 48 | 11 | 0.23 |
| 1427 | Andrej Ruppersberger | 4 | 4 | 11 | 3 | 0.23 |
| 1428 | Chao Qin | 4 | 4 | 11 | 3 | 0.23 |
| 1429 | Honoré Foucher | 4 | 4 | 11 | 3 | 0.23 |
| 1430 | Kevin Baker | 4 | 4 | 11 | 3 | 0.23 |
| 1431 | Maura Jovinelli | 4 | 4 | 11 | 3 | 0.23 |
| 1432 | Zachary Francis | 4 | 4 | 11 | 3 | 0.23 |
| 1433 | Lunar Drift | 3 | 2 | 39 | 9 | 0.23 |
| 1434 | Synaptic Collapse | 4 | 4 | 7 | 4 | 0.23 |
| 1435 | Shared Secrets | 3 | 3 | 29 | 7 | 0.23 |
| 1436 | Yong Guo | 2 | 2 | 51 | 10 | 0.23 |
| 1437 | Janina Kałek | 4 | 4 | 14 | 2 | 0.23 |
| 1438 | Lei Zhu | 4 | 4 | 14 | 2 | 0.23 |
| 1439 | Coriolano Luria-Scialpi | 3 | 3 | 25 | 8 | 0.23 |
| 1440 | Wulf Lübs | 3 | 3 | 36 | 5 | 0.23 |
| 1441 | Yan Chang | 3 | 3 | 36 | 5 | 0.23 |
| 1442 | Alexa Albers-Säuberlich | 3 | 3 | 32 | 6 | 0.23 |
| 1443 | Nordisk Resonans | 3 | 3 | 32 | 6 | 0.23 |
| 1444 | Peter Jacobi Jäckel | 3 | 3 | 32 | 6 | 0.23 |
| 1445 | Prisma Flux | 3 | 3 | 32 | 6 | 0.23 |
| 1446 | Samantha Herring | 3 | 3 | 32 | 6 | 0.23 |
| 1447 | Scott Mckinney | 3 | 3 | 32 | 6 | 0.23 |
| 1448 | Terry Gonzalez | 3 | 3 | 32 | 6 | 0.23 |
| 1449 | Jamie Ramos | 4 | 4 | 6 | 4 | 0.23 |
| 1450 | Ricky Silva | 4 | 4 | 6 | 4 | 0.23 |
| 1451 | Sonic Pulse | 4 | 4 | 6 | 4 | 0.23 |
| 1452 | Min Yin | 4 | 4 | 17 | 1 | 0.23 |
| 1453 | Yang Yi | 4 | 4 | 17 | 1 | 0.23 |
| 1454 | Gang Zeng | 4 | 3 | 23 | 4 | 0.23 |
| 1455 | Amanda Blake | 3 | 3 | 39 | 4 | 0.23 |
| 1456 | Tao Song | 3 | 3 | 39 | 4 | 0.23 |
| 1457 | Qiang Ye | 3 | 3 | 35 | 5 | 0.23 |
| 1458 | Xia Fan | 3 | 3 | 35 | 5 | 0.23 |
| 1459 | Yang Gao | 3 | 3 | 35 | 5 | 0.23 |
| 1460 | Yang Kong | 4 | 4 | 20 | 0 | 0.23 |
| 1461 | Qiang Xiao | 4 | 3 | 26 | 3 | 0.23 |
| 1462 | Li Tang | 3 | 3 | 31 | 6 | 0.23 |
| 1463 | Ping Cao | 3 | 3 | 31 | 6 | 0.23 |
| 1464 | Thomas Harrison | 3 | 3 | 31 | 6 | 0.23 |
| 1465 | Beth Carpenter | 3 | 2 | 37 | 9 | 0.23 |
| 1466 | Seth Smith | 3 | 2 | 37 | 9 | 0.23 |
| 1467 | Jie Dai | 2 | 2 | 53 | 9 | 0.23 |
| 1468 | Gang Ye | 4 | 4 | 16 | 1 | 0.23 |
| 1469 | Li Ye | 4 | 4 | 16 | 1 | 0.23 |
| 1470 | Léon Pasquier | 4 | 4 | 16 | 1 | 0.23 |
| 1471 | Yoko Fujita | 4 | 4 | 16 | 1 | 0.23 |
| 1472 | Denise Johnson | 1 | 1 | 71 | 13 | 0.23 |
| 1473 | Donna Malone | 1 | 1 | 71 | 13 | 0.23 |
| 1474 | Gang Tao | 1 | 1 | 71 | 13 | 0.23 |
| 1475 | Tao Zhu | 4 | 4 | 19 | 0 | 0.23 |
| 1476 | Justin King | 3 | 3 | 30 | 6 | 0.23 |
| 1477 | Ming Su | 2 | 2 | 52 | 9 | 0.23 |
| 1478 | Xiulan Shao | 4 | 4 | 15 | 1 | 0.23 |
| 1479 | Xiuying Yan | 4 | 4 | 15 | 1 | 0.23 |
| 1480 | Crimson Carriage | 7 | 2 | 4 | 0 | 0.23 |
| 1481 | Rainfall Fiction | 6 | 3 | 3 | 0 | 0.23 |
| 1482 | Gang Hu | 3 | 3 | 33 | 5 | 0.23 |
| 1483 | Guiying Yi | 3 | 3 | 33 | 5 | 0.23 |
| 1484 | Janine Berger | 4 | 4 | 7 | 3 | 0.23 |
| 1485 | Ming Cai | 4 | 4 | 7 | 3 | 0.23 |
| 1486 | Jun Tian | 4 | 4 | 18 | 0 | 0.23 |
| 1487 | Gang Mao | 4 | 4 | 14 | 1 | 0.22 |
| 1488 | Li Cui | 4 | 4 | 14 | 1 | 0.22 |
| 1489 | Tao Zou | 4 | 4 | 14 | 1 | 0.22 |
| 1490 | Xiulan Zou | 4 | 4 | 14 | 1 | 0.22 |
| 1491 | Mutual Orbit | 2 | 2 | 47 | 10 | 0.22 |
| 1492 | Qiang Kang | 4 | 4 | 10 | 2 | 0.22 |
| 1493 | Rhea Wali | 4 | 4 | 10 | 2 | 0.22 |
| 1494 | Adrian Carroll | 2 | 2 | 21 | 17 | 0.22 |
| 1495 | Christopher Rice | 3 | 3 | 32 | 5 | 0.22 |
| 1496 | Fallen Cherubs | 3 | 3 | 32 | 5 | 0.22 |
| 1497 | Yang Guo | 3 | 3 | 32 | 5 | 0.22 |
| 1498 | Nichole Martinez | 2 | 2 | 32 | 14 | 0.22 |
| 1499 | William Mcclain | 4 | 4 | 6 | 3 | 0.22 |
| 1500 | Ellen Ford | 4 | 3 | 12 | 6 | 0.22 |
| 1501 | Chao Bai | 4 | 4 | 17 | 0 | 0.22 |
| 1502 | Chao Ye | 4 | 3 | 23 | 3 | 0.22 |
| 1503 | Ping Cheng | 3 | 3 | 28 | 6 | 0.22 |
| 1504 | Thomas Walsh | 2 | 2 | 50 | 9 | 0.22 |
| 1505 | Coastal Horizon | 4 | 4 | 13 | 1 | 0.22 |
| 1506 | Crimson Theorem | 4 | 4 | 13 | 1 | 0.22 |
| 1507 | Lei Lu | 4 | 4 | 13 | 1 | 0.22 |
| 1508 | Na Zhang | 3 | 3 | 31 | 5 | 0.22 |
| 1509 | Ursus | 3 | 3 | 31 | 5 | 0.22 |
| 1510 | Sylas Dune | 5 | 4 | 0 | 0 | 0.22 |
| 1511 | Min Chang | 4 | 4 | 16 | 0 | 0.22 |
| 1512 | Pamela Chan | 3 | 3 | 27 | 6 | 0.22 |
| 1513 | Guiying Yin | 4 | 3 | 18 | 4 | 0.22 |
| 1514 | Nicole Sudak | 4 | 3 | 18 | 4 | 0.22 |
| 1515 | Henriette Gonzalez-Grégoire | 1 | 1 | 60 | 15 | 0.22 |
| 1516 | Laurent-Théodore Humbert | 1 | 1 | 60 | 15 | 0.22 |
| 1517 | Philip Schneider | 1 | 1 | 60 | 15 | 0.22 |
| 1518 | Édith Deschamps Le Clément | 1 | 1 | 60 | 15 | 0.22 |
| 1519 | Chao Jia | 3 | 3 | 34 | 4 | 0.22 |
| 1520 | Gang Kang | 3 | 3 | 34 | 4 | 0.22 |
| 1521 | Steven Smith | 3 | 3 | 34 | 4 | 0.22 |
| 1522 | Wei Chang | 3 | 3 | 34 | 4 | 0.22 |
| 1523 | Samar Agarwal | 1 | 1 | 34 | 22 | 0.22 |
| 1524 | Stephanie Robinson | 4 | 4 | 8 | 2 | 0.22 |
| 1525 | Stephen Meyer | 4 | 4 | 8 | 2 | 0.22 |
| 1526 | Juan Shao | 4 | 3 | 25 | 2 | 0.22 |
| 1527 | Surveillance | 3 | 3 | 30 | 5 | 0.22 |
| 1528 | Jing Shen | 3 | 3 | 37 | 3 | 0.22 |
| 1529 | Min Dai | 3 | 3 | 37 | 3 | 0.22 |
| 1530 | Shirley Riley | 3 | 3 | 22 | 7 | 0.22 |
| 1531 | Tao Cai | 3 | 3 | 33 | 4 | 0.22 |
| 1532 | Buzz Collective | 4 | 4 | 7 | 2 | 0.22 |
| 1533 | Diana Taylor | 4 | 4 | 7 | 2 | 0.22 |
| 1534 | Franck Prévost de la Bertrand | 4 | 4 | 7 | 2 | 0.22 |
| 1535 | Kayla Gomez | 4 | 4 | 7 | 2 | 0.22 |
| 1536 | Pénélope du Cohen | 4 | 4 | 7 | 2 | 0.22 |
| 1537 | Ming Chang | 3 | 3 | 29 | 5 | 0.22 |
| 1538 | Anita Hamerla | 4 | 4 | 3 | 3 | 0.22 |
| 1539 | Xia Tang | 4 | 4 | 14 | 0 | 0.22 |
| 1540 | Maria Black | 3 | 3 | 25 | 6 | 0.22 |
| 1541 | Yong Hao | 2 | 2 | 36 | 12 | 0.22 |
| 1542 | Xia Feng | 3 | 3 | 32 | 4 | 0.22 |
| 1543 | Jun Chen | 3 | 3 | 28 | 5 | 0.22 |
| 1544 | Danielle Walsh | 2 | 2 | 28 | 14 | 0.22 |
| 1545 | Li Zhang | 2 | 2 | 28 | 14 | 0.22 |
| 1546 | Kumiko Miura | 4 | 4 | 2 | 3 | 0.22 |
| 1547 | Ashley Yang | 2 | 2 | 50 | 8 | 0.22 |
| 1548 | Christopher Andrews | 2 | 2 | 50 | 8 | 0.22 |
| 1549 | Jeffrey Herring | 2 | 2 | 50 | 8 | 0.22 |
| 1550 | Li Li | 4 | 4 | 13 | 0 | 0.22 |
| 1551 | Wei Mao | 4 | 4 | 13 | 0 | 0.22 |
| 1552 | Yan Gong | 3 | 3 | 24 | 6 | 0.22 |
| 1553 | Yong Xue | 3 | 3 | 35 | 3 | 0.22 |
| 1554 | Juan Lu | 2 | 2 | 46 | 9 | 0.22 |
| 1555 | Xiuying Duan | 4 | 3 | 22 | 2 | 0.22 |
| 1556 | Arco Luminoso | 3 | 3 | 27 | 5 | 0.22 |
| 1557 | Ming Du | 3 | 3 | 27 | 5 | 0.22 |
| 1558 | Philippine Laurent | 3 | 3 | 27 | 5 | 0.22 |
| 1559 | Xia Qiao | 3 | 3 | 27 | 5 | 0.22 |
| 1560 | Ming Wen | 4 | 4 | 12 | 0 | 0.22 |
| 1561 | Lei Tao | 4 | 2 | 35 | 3 | 0.22 |
| 1562 | Aneta Pruschke-Sölzer | 3 | 3 | 23 | 6 | 0.22 |
| 1563 | Jessica Peck | 3 | 3 | 23 | 6 | 0.22 |
| 1564 | Maria Carlson | 3 | 3 | 23 | 6 | 0.22 |
| 1565 | Na Qin | 3 | 3 | 23 | 6 | 0.22 |
| 1566 | Katelyn Johnson | 3 | 3 | 34 | 3 | 0.22 |
| 1567 | Sarah Wheeler | 3 | 3 | 34 | 3 | 0.22 |
| 1568 | Donald Medina | 2 | 2 | 45 | 9 | 0.21 |
| 1569 | Erik Mathews | 2 | 2 | 45 | 9 | 0.21 |
| 1570 | Joshua Orozco | 2 | 2 | 45 | 9 | 0.21 |
| 1571 | Sander Veenstra | 2 | 2 | 45 | 9 | 0.21 |
| 1572 | Estación Sonora | 3 | 3 | 30 | 4 | 0.21 |
| 1573 | Guiying Gu | 3 | 3 | 30 | 4 | 0.21 |
| 1574 | Yang Fan | 3 | 3 | 30 | 4 | 0.21 |
| 1575 | Yang Liu | 2 | 2 | 30 | 13 | 0.21 |
| 1576 | Christina Johnson | 4 | 4 | 4 | 2 | 0.21 |
| 1577 | Cynthia Murphy | 4 | 4 | 4 | 2 | 0.21 |
| 1578 | Derek Smith | 4 | 4 | 4 | 2 | 0.21 |
| 1579 | Julie Davis | 4 | 4 | 4 | 2 | 0.21 |
| 1580 | Raissa Anders | 4 | 4 | 4 | 2 | 0.21 |
| 1581 | Kimberly Stanton | 3 | 3 | 26 | 5 | 0.21 |
| 1582 | Yan Jia | 3 | 3 | 26 | 5 | 0.21 |
| 1583 | Xia Pan | 4 | 3 | 17 | 3 | 0.21 |
| 1584 | Luigina Camuccini | 3 | 3 | 22 | 6 | 0.21 |
| 1585 | Yan Song | 3 | 3 | 22 | 6 | 0.21 |
| 1586 | Scott Snyder | 2 | 2 | 33 | 12 | 0.21 |
| 1587 | Jie Li | 3 | 3 | 29 | 4 | 0.21 |
| 1588 | Lei Huang | 3 | 3 | 29 | 4 | 0.21 |
| 1589 | Marina Acedo Montaña | 3 | 3 | 29 | 4 | 0.21 |
| 1590 | Selma Flantz | 3 | 3 | 29 | 4 | 0.21 |
| 1591 | Velvet Haze | 3 | 3 | 29 | 4 | 0.21 |
| 1592 | Yang Zeng | 3 | 3 | 25 | 5 | 0.21 |
| 1593 | Samantha Mills | 2 | 2 | 47 | 8 | 0.21 |
| 1594 | Yan Tao | 2 | 2 | 47 | 8 | 0.21 |
| 1595 | Maria Tyler | 3 | 3 | 21 | 6 | 0.21 |
| 1596 | Gang Gao | 2 | 2 | 54 | 6 | 0.21 |
| 1597 | Leandro Artigas Benítez | 3 | 3 | 28 | 4 | 0.21 |
| 1598 | Xia Tian | 3 | 3 | 28 | 4 | 0.21 |
| 1599 | Chao Kong | 3 | 2 | 34 | 7 | 0.21 |
| 1600 | Steven Buchanan | 4 | 4 | 2 | 2 | 0.21 |
| 1601 | Yong Fan | 4 | 3 | 19 | 2 | 0.21 |
| 1602 | David Moore | 3 | 3 | 24 | 5 | 0.21 |
| 1603 | Xiulan Zhong | 3 | 3 | 24 | 5 | 0.21 |
| 1604 | Yan Fu | 3 | 3 | 35 | 2 | 0.21 |
| 1605 | Yong Cui | 2 | 2 | 46 | 8 | 0.21 |
| 1606 | Xia Zhang | 4 | 4 | 9 | 0 | 0.21 |
| 1607 | Rolando Gagliardi | 4 | 2 | 21 | 6 | 0.21 |
| 1608 | Amber Bates | 1 | 1 | 57 | 14 | 0.21 |
| 1609 | April Schmidt | 1 | 1 | 57 | 14 | 0.21 |
| 1610 | Cody Patterson | 1 | 1 | 57 | 14 | 0.21 |
| 1611 | Colleen Velazquez | 1 | 1 | 57 | 14 | 0.21 |
| 1612 | Jeremy Park | 1 | 1 | 57 | 14 | 0.21 |
| 1613 | William Keller | 1 | 1 | 57 | 14 | 0.21 |
| 1614 | Alfredo Ajello | 3 | 2 | 37 | 6 | 0.21 |
| 1615 | Jun Liu | 3 | 2 | 37 | 6 | 0.21 |
| 1616 | Ethereal Chorus | 2 | 2 | 49 | 7 | 0.21 |
| 1617 | Makayla Stone | 4 | 3 | 14 | 3 | 0.21 |
| 1618 | Chao Fang | 3 | 3 | 30 | 3 | 0.21 |
| 1619 | Fang Wan | 3 | 3 | 30 | 3 | 0.21 |
| 1620 | Jun Deng | 3 | 3 | 30 | 3 | 0.21 |
| 1621 | Xiulan Xiang | 2 | 2 | 41 | 9 | 0.21 |
| 1622 | Chao Song | 4 | 3 | 17 | 2 | 0.21 |
| 1623 | Dennis Bush | 3 | 3 | 22 | 5 | 0.21 |
| 1624 | Rebecca Chapman | 2 | 2 | 22 | 14 | 0.21 |
| 1625 | Gang Lai | 2 | 2 | 44 | 8 | 0.21 |
| 1626 | Levi Holloway | 4 | 4 | 7 | 0 | 0.21 |
| 1627 | Jie Shen | 3 | 3 | 29 | 3 | 0.21 |
| 1628 | Juan Zhang | 3 | 3 | 29 | 3 | 0.21 |
| 1629 | Ming Liang | 3 | 3 | 29 | 3 | 0.21 |
| 1630 | Yan Kong | 3 | 3 | 29 | 3 | 0.21 |
| 1631 | Ming Shi | 2 | 2 | 40 | 9 | 0.21 |
| 1632 | Kelly Johnson | 2 | 2 | 51 | 6 | 0.21 |
| 1633 | Fang Hao | 3 | 3 | 25 | 4 | 0.21 |
| 1634 | Michael Pratt | 3 | 3 | 25 | 4 | 0.21 |
| 1635 | Xiulan Feng | 3 | 3 | 25 | 4 | 0.21 |
| 1636 | Ming Jia | 5 | 2 | 17 | 2 | 0.21 |
| 1637 | Charles Wright | 2 | 2 | 32 | 11 | 0.21 |
| 1638 | Jonah Calloway | 4 | 4 | 6 | 0 | 0.21 |
| 1639 | Marin Thorne | 4 | 4 | 6 | 0 | 0.21 |
| 1640 | Na Feng | 4 | 3 | 23 | 0 | 0.21 |
| 1641 | Tao Meng | 3 | 3 | 28 | 3 | 0.21 |
| 1642 | Wei Guo | 3 | 3 | 28 | 3 | 0.21 |
| 1643 | Michael Sexton | 2 | 2 | 39 | 9 | 0.20 |
| 1644 | Robert Jenkins | 2 | 2 | 39 | 9 | 0.20 |
| 1645 | Jie Xie | 4 | 3 | 19 | 1 | 0.20 |
| 1646 | Min Peng | 3 | 3 | 24 | 4 | 0.20 |
| 1647 | Puccio Bixio-Gatto | 3 | 3 | 24 | 4 | 0.20 |
| 1648 | Taichi Watanabe | 3 | 3 | 24 | 4 | 0.20 |
| 1649 | Kamila Ornat | 2 | 2 | 20 | 14 | 0.20 |
| 1650 | Marie James | 2 | 2 | 20 | 14 | 0.20 |
| 1651 | Mary Rodriguez | 2 | 2 | 20 | 14 | 0.20 |
| 1652 | Eckehard Wagner | 3 | 3 | 16 | 6 | 0.20 |
| 1653 | Juan Hu | 3 | 3 | 27 | 3 | 0.20 |
| 1654 | Ming Song | 3 | 2 | 44 | 3 | 0.20 |
| 1655 | Hansjürgen Börner | 2 | 2 | 38 | 9 | 0.20 |
| 1656 | Michael Gomez | 2 | 2 | 49 | 6 | 0.20 |
| 1657 | Jie He | 3 | 3 | 23 | 4 | 0.20 |
| 1658 | Whispered Embers | 3 | 3 | 23 | 4 | 0.20 |
| 1659 | Kristen Parks | 3 | 3 | 19 | 5 | 0.20 |
| 1660 | Whisper the Thistles | 3 | 3 | 19 | 5 | 0.20 |
| 1661 | Jing Li | 3 | 3 | 30 | 2 | 0.20 |
| 1662 | Megan Sandoval | 2 | 2 | 30 | 11 | 0.20 |
| 1663 | The Phantom Operators | 5 | 3 | 5 | 0 | 0.20 |
| 1664 | Astrid Nørgaard | 4 | 4 | 4 | 0 | 0.20 |
| 1665 | Barnaby Quill | 4 | 4 | 4 | 0 | 0.20 |
| 1666 | Jonas Fenwick | 4 | 4 | 4 | 0 | 0.20 |
| 1667 | Marina Grey | 4 | 4 | 4 | 0 | 0.20 |
| 1668 | Orin Caldwell | 4 | 4 | 4 | 0 | 0.20 |
| 1669 | Robin Jones | 4 | 4 | 4 | 0 | 0.20 |
| 1670 | Selena Marrow | 4 | 4 | 4 | 0 | 0.20 |
| 1671 | Silas Finch | 4 | 4 | 4 | 0 | 0.20 |
| 1672 | Thorne Rivenhall | 4 | 4 | 4 | 0 | 0.20 |
| 1673 | Lei Dai | 3 | 3 | 26 | 3 | 0.20 |
| 1674 | Fang Lai | 2 | 2 | 48 | 6 | 0.20 |
| 1675 | Christopher Murray | 1 | 1 | 59 | 12 | 0.20 |
| 1676 | James Rubio | 1 | 1 | 59 | 12 | 0.20 |
| 1677 | Meredith Walker | 1 | 1 | 59 | 12 | 0.20 |
| 1678 | Rebecca Gonzales | 1 | 1 | 59 | 12 | 0.20 |
| 1679 | Laura Braun | 2 | 2 | 33 | 10 | 0.20 |
| 1680 | Lisa Miller | 2 | 2 | 44 | 7 | 0.20 |
| 1681 | Stacey Taylor | 3 | 3 | 14 | 6 | 0.20 |
| 1682 | Diana Mitchell | 1 | 1 | 62 | 11 | 0.20 |
| 1683 | James Hall | 1 | 1 | 62 | 11 | 0.20 |
| 1684 | Kevin Lopez | 1 | 1 | 62 | 11 | 0.20 |
| 1685 | Jing Tang | 3 | 3 | 25 | 3 | 0.20 |
| 1686 | Juan Zheng | 3 | 3 | 25 | 3 | 0.20 |
| 1687 | Li Xu | 3 | 3 | 25 | 3 | 0.20 |
| 1688 | Min Tan | 3 | 3 | 25 | 3 | 0.20 |
| 1689 | Xiulan Huang | 3 | 3 | 25 | 3 | 0.20 |
| 1690 | Chao Chang | 4 | 3 | 16 | 1 | 0.20 |
| 1691 | Jie Yi | 3 | 3 | 21 | 4 | 0.20 |
| 1692 | Lei Lin | 3 | 3 | 21 | 4 | 0.20 |
| 1693 | Emmy Bonbach | 4 | 3 | 12 | 2 | 0.20 |
| 1694 | Herr Heinz-Walter Scheuermann | 4 | 3 | 12 | 2 | 0.20 |
| 1695 | Jie Cheng | 4 | 3 | 12 | 2 | 0.20 |
| 1696 | Paige Adams | 3 | 3 | 13 | 6 | 0.20 |
| 1697 | Ping Tan | 3 | 3 | 24 | 3 | 0.20 |
| 1698 | Qiang Zeng | 3 | 3 | 24 | 3 | 0.20 |
| 1699 | Stephanie Huhn | 3 | 3 | 24 | 3 | 0.20 |
| 1700 | Xiuying Ma | 3 | 3 | 24 | 3 | 0.20 |
| 1701 | Li Jiang | 3 | 3 | 27 | 2 | 0.20 |
| 1702 | Tao Liu | 3 | 3 | 27 | 2 | 0.20 |
| 1703 | Xiuying Ren | 3 | 3 | 27 | 2 | 0.20 |
| 1704 | Bertram Hübel | 3 | 3 | 23 | 3 | 0.20 |
| 1705 | Gang Tang | 3 | 3 | 23 | 3 | 0.20 |
| 1706 | Guiying Xiao | 3 | 3 | 23 | 3 | 0.20 |
| 1707 | Lei Shao | 3 | 3 | 23 | 3 | 0.20 |
| 1708 | Lei Shi | 3 | 3 | 23 | 3 | 0.20 |
| 1709 | Li Zhao | 3 | 3 | 23 | 3 | 0.20 |
| 1710 | Ming Wei | 3 | 3 | 23 | 3 | 0.20 |
| 1711 | Jie Mao | 3 | 3 | 19 | 4 | 0.20 |
| 1712 | Tracy Lawson | 2 | 2 | 41 | 7 | 0.20 |
| 1713 | Andrew Miller | 1 | 1 | 52 | 13 | 0.20 |
| 1714 | Robert Martinez | 1 | 1 | 52 | 13 | 0.20 |
| 1715 | Samuel Morrison | 1 | 1 | 52 | 13 | 0.20 |
| 1716 | Iron Cathedral | 7 | 1 | 3 | 0 | 0.20 |
| 1717 | Chao Wang | 3 | 3 | 26 | 2 | 0.20 |
| 1718 | Fang Jiang | 3 | 3 | 26 | 2 | 0.20 |
| 1719 | Oscar Marshall | 3 | 3 | 26 | 2 | 0.20 |
| 1720 | Ping Xie | 3 | 3 | 26 | 2 | 0.20 |
| 1721 | Xia Lei | 3 | 3 | 26 | 2 | 0.20 |
| 1722 | Xiuying Qin | 3 | 3 | 26 | 2 | 0.20 |
| 1723 | Kristýna Horváthová | 4 | 4 | 0 | 0 | 0.20 |
| 1724 | Fiesta Nocturna | 3 | 3 | 22 | 3 | 0.20 |
| 1725 | Harmonic Collective | 3 | 3 | 22 | 3 | 0.20 |
| 1726 | Robert Pham | 3 | 3 | 22 | 3 | 0.20 |
| 1727 | Rómulo Huertas | 3 | 3 | 22 | 3 | 0.20 |
| 1728 | Tao Du | 3 | 3 | 22 | 3 | 0.20 |
| 1729 | Tao Kong | 3 | 3 | 22 | 3 | 0.20 |
| 1730 | Xiulan Yin | 3 | 3 | 22 | 3 | 0.20 |
| 1731 | Yan Hou | 3 | 3 | 22 | 3 | 0.20 |
| 1732 | Yang Dai | 3 | 3 | 22 | 3 | 0.20 |
| 1733 | Qiang Cheng | 4 | 3 | 13 | 1 | 0.19 |
| 1734 | Olga Kosałka | 3 | 3 | 7 | 7 | 0.19 |
| 1735 | Preset Protocol | 3 | 3 | 7 | 7 | 0.19 |
| 1736 | Flora Karz | 3 | 3 | 18 | 4 | 0.19 |
| 1737 | Glide | 3 | 3 | 18 | 4 | 0.19 |
| 1738 | Ryan Cohen | 3 | 3 | 18 | 4 | 0.19 |
| 1739 | Yong Ding | 3 | 3 | 18 | 4 | 0.19 |
| 1740 | Guiying Dong | 3 | 3 | 29 | 1 | 0.19 |
| 1741 | Yui Fukuda | 3 | 3 | 14 | 5 | 0.19 |
| 1742 | Jing Deng | 3 | 3 | 25 | 2 | 0.19 |
| 1743 | Mira Everly | 5 | 3 | 0 | 0 | 0.19 |
| 1744 | Juan Johnson | 3 | 3 | 21 | 3 | 0.19 |
| 1745 | Lei Du | 3 | 3 | 21 | 3 | 0.19 |
| 1746 | Na Mo | 3 | 3 | 21 | 3 | 0.19 |
| 1747 | Carl Jones | 2 | 2 | 32 | 9 | 0.19 |
| 1748 | Christina Bowers | 2 | 2 | 32 | 9 | 0.19 |
| 1749 | Beverly Olsen | 1 | 1 | 54 | 12 | 0.19 |
| 1750 | Lisa Woods | 1 | 1 | 54 | 12 | 0.19 |
| 1751 | Rei Aoki | 1 | 1 | 54 | 12 | 0.19 |
| 1752 | Vasyl Jaroš | 3 | 2 | 23 | 7 | 0.19 |
| 1753 | Sem de Swart-van Voorst | 2 | 2 | 39 | 7 | 0.19 |
| 1754 | Antonietta Zaccagnini | 3 | 3 | 13 | 5 | 0.19 |
| 1755 | Gang Cai | 3 | 3 | 24 | 2 | 0.19 |
| 1756 | Gang Tian | 3 | 3 | 24 | 2 | 0.19 |
| 1757 | Jing Du | 3 | 3 | 24 | 2 | 0.19 |
| 1758 | Ming Hou | 3 | 3 | 24 | 2 | 0.19 |
| 1759 | Qiang Feng | 3 | 3 | 24 | 2 | 0.19 |
| 1760 | Xiulan Meng | 3 | 3 | 24 | 2 | 0.19 |
| 1761 | Ashley Andrade | 1 | 1 | 57 | 11 | 0.19 |
| 1762 | Darrell Wilson | 1 | 1 | 57 | 11 | 0.19 |
| 1763 | Laura Moore | 1 | 1 | 57 | 11 | 0.19 |
| 1764 | Timothy Lin | 1 | 1 | 57 | 11 | 0.19 |
| 1765 | Xia Long | 3 | 3 | 20 | 3 | 0.19 |
| 1766 | Ingbert Hertrampf | 2 | 2 | 31 | 9 | 0.19 |
| 1767 | Patricia-Julie Lopes | 3 | 3 | 16 | 4 | 0.19 |
| 1768 | Guiying Ma | 3 | 3 | 23 | 2 | 0.19 |
| 1769 | Jordan Baxter | 3 | 3 | 23 | 2 | 0.19 |
| 1770 | Natasza Dydo | 3 | 3 | 23 | 2 | 0.19 |
| 1771 | Yang Liang | 3 | 3 | 23 | 2 | 0.19 |
| 1772 | Katrina Hendricks | 3 | 3 | 8 | 6 | 0.19 |
| 1773 | Edward Siering | 3 | 3 | 19 | 3 | 0.19 |
| 1774 | Jun Yuan | 3 | 3 | 19 | 3 | 0.19 |
| 1775 | Lunar Pulse | 3 | 3 | 19 | 3 | 0.19 |
| 1776 | Vicki Morgan | 3 | 3 | 19 | 3 | 0.19 |
| 1777 | Gerlind Sager-Ortmann | 3 | 2 | 36 | 3 | 0.19 |
| 1778 | Wei Tao | 2 | 2 | 41 | 6 | 0.19 |
| 1779 | Yang Cao | 2 | 2 | 41 | 6 | 0.19 |
| 1780 | Jonathan Diaz | 4 | 3 | 10 | 1 | 0.19 |
| 1781 | Timothy Rios | 3 | 3 | 15 | 4 | 0.19 |
| 1782 | Brandi Daugherty | 1 | 1 | 63 | 9 | 0.19 |
| 1783 | David Mueller | 1 | 1 | 63 | 9 | 0.19 |
| 1784 | Donna Davidson | 1 | 1 | 63 | 9 | 0.19 |
| 1785 | Jennifer Thomas | 1 | 1 | 63 | 9 | 0.19 |
| 1786 | Joseph Choi | 1 | 1 | 63 | 9 | 0.19 |
| 1787 | Joseph Huang | 1 | 1 | 63 | 9 | 0.19 |
| 1788 | Linda Williams | 1 | 1 | 63 | 9 | 0.19 |
| 1789 | Peter Johnson | 1 | 1 | 63 | 9 | 0.19 |
| 1790 | Raymond Marshall | 1 | 1 | 63 | 9 | 0.19 |
| 1791 | Shannon Hughes | 1 | 1 | 63 | 9 | 0.19 |
| 1792 | Stacy Saunders | 1 | 1 | 63 | 9 | 0.19 |
| 1793 | Tiffany Acevedo | 1 | 1 | 63 | 9 | 0.19 |
| 1794 | Adalbert Adolph | 3 | 3 | 11 | 5 | 0.19 |
| 1795 | Chao Cui | 3 | 3 | 22 | 2 | 0.19 |
| 1796 | Na Bai | 3 | 3 | 22 | 2 | 0.19 |
| 1797 | Wei Yin | 3 | 3 | 22 | 2 | 0.19 |
| 1798 | Xiulan Gu | 3 | 3 | 22 | 2 | 0.19 |
| 1799 | Xiulan Jia | 3 | 3 | 22 | 2 | 0.19 |
| 1800 | Xiuying Wang | 3 | 3 | 22 | 2 | 0.19 |
| 1801 | Yan Cui | 3 | 3 | 22 | 2 | 0.19 |
| 1802 | Civic Ensemble | 2 | 2 | 44 | 5 | 0.19 |
| 1803 | Elizabeth Wagner | 2 | 2 | 44 | 5 | 0.19 |
| 1804 | Bianca Sagnelli-Onio | 3 | 3 | 18 | 3 | 0.19 |
| 1805 | Christine Wall | 3 | 3 | 18 | 3 | 0.19 |
| 1806 | Fernanda Guarneri | 3 | 3 | 18 | 3 | 0.19 |
| 1807 | Ping Lei | 3 | 3 | 18 | 3 | 0.19 |
| 1808 | Rhythmic Echo | 3 | 3 | 18 | 3 | 0.19 |
| 1809 | Leslie Moore | 2 | 2 | 29 | 9 | 0.19 |
| 1810 | Archipelago | 3 | 3 | 14 | 4 | 0.19 |
| 1811 | Yang Zou | 3 | 3 | 25 | 1 | 0.19 |
| 1812 | Chao Shi | 3 | 3 | 21 | 2 | 0.19 |
| 1813 | Guiying Zheng | 3 | 3 | 21 | 2 | 0.19 |
| 1814 | Jie Zhong | 3 | 3 | 21 | 2 | 0.19 |
| 1815 | Jun Gu | 3 | 3 | 21 | 2 | 0.19 |
| 1816 | Jun Shen | 3 | 3 | 21 | 2 | 0.19 |
| 1817 | Tao Xiong | 3 | 3 | 21 | 2 | 0.19 |
| 1818 | Tao Zhao | 3 | 2 | 38 | 2 | 0.19 |
| 1819 | Christopher Davis | 3 | 3 | 17 | 3 | 0.19 |
| 1820 | Jing Xiang | 3 | 3 | 17 | 3 | 0.19 |
| 1821 | Rhythm Brothers | 3 | 3 | 17 | 3 | 0.19 |
| 1822 | Yong Zhong | 4 | 2 | 25 | 1 | 0.19 |
| 1823 | Akemi Nakajima | 3 | 3 | 13 | 4 | 0.19 |
| 1824 | Annetta Passalacqua | 4 | 3 | 4 | 2 | 0.19 |
| 1825 | Olaf Szumny | 3 | 3 | 9 | 5 | 0.19 |
| 1826 | Chao Cheng | 3 | 3 | 20 | 2 | 0.19 |
| 1827 | Chao Shen | 3 | 3 | 20 | 2 | 0.19 |
| 1828 | Min Yi | 3 | 3 | 20 | 2 | 0.19 |
| 1829 | Yang Qiao | 3 | 3 | 20 | 2 | 0.19 |
| 1830 | Yong Dai | 3 | 3 | 20 | 2 | 0.19 |
| 1831 | Konrad Meissner | 3 | 3 | 16 | 3 | 0.19 |
| 1832 | Na Luo | 3 | 3 | 16 | 3 | 0.19 |
| 1833 | Sovereign Riders | 3 | 3 | 16 | 3 | 0.19 |
| 1834 | Fang Xie | 2 | 2 | 38 | 6 | 0.18 |
| 1835 | Min Xu | 2 | 2 | 38 | 6 | 0.18 |
| 1836 | Clinton Fischer | 1 | 1 | 49 | 12 | 0.18 |
| 1837 | David Allison | 1 | 1 | 49 | 12 | 0.18 |
| 1838 | Erica Lopez | 1 | 1 | 49 | 12 | 0.18 |
| 1839 | Franck Joly | 1 | 1 | 49 | 12 | 0.18 |
| 1840 | Melissa Rivas | 1 | 1 | 49 | 12 | 0.18 |
| 1841 | Benoît-Zacharie Gilbert | 3 | 3 | 12 | 4 | 0.18 |
| 1842 | Bianca Weber | 3 | 3 | 12 | 4 | 0.18 |
| 1843 | Margaud Chevallier | 3 | 3 | 12 | 4 | 0.18 |
| 1844 | Nathalie Jacquot | 3 | 3 | 12 | 4 | 0.18 |
| 1845 | Sly Notion | 3 | 3 | 12 | 4 | 0.18 |
| 1846 | Jing Hu | 2 | 2 | 34 | 7 | 0.18 |
| 1847 | Luminescence | 3 | 3 | 8 | 5 | 0.18 |
| 1848 | Marc-Raymond Durand | 3 | 3 | 8 | 5 | 0.18 |
| 1849 | Sync Shift | 3 | 3 | 8 | 5 | 0.18 |
| 1850 | Bureaucracy | 3 | 3 | 19 | 2 | 0.18 |
| 1851 | Karl-Otto Käster | 3 | 3 | 19 | 2 | 0.18 |
| 1852 | Robert Stephens | 3 | 3 | 19 | 2 | 0.18 |
| 1853 | Xiulan Xie | 3 | 3 | 19 | 2 | 0.18 |
| 1854 | Yang Xie | 3 | 3 | 19 | 2 | 0.18 |
| 1855 | Phantom Roots | 2 | 2 | 30 | 8 | 0.18 |
| 1856 | Lei Wei | 3 | 3 | 15 | 3 | 0.18 |
| 1857 | Yan Wu | 3 | 3 | 15 | 3 | 0.18 |
| 1858 | Stacie Bennett | 2 | 2 | 37 | 6 | 0.18 |
| 1859 | Pier Pavone-Cignaroli | 1 | 1 | 48 | 12 | 0.18 |
| 1860 | Charles Chase | 3 | 3 | 11 | 4 | 0.18 |
| 1861 | Clara Seco-Pelayo | 3 | 3 | 11 | 4 | 0.18 |
| 1862 | Lina Mendizábal Robledo | 3 | 2 | 17 | 7 | 0.18 |
| 1863 | Qiang Sun | 3 | 3 | 22 | 1 | 0.18 |
| 1864 | Xiulan Hu | 3 | 3 | 22 | 1 | 0.18 |
| 1865 | Reginald Wallace | 2 | 2 | 33 | 7 | 0.18 |
| 1866 | Audrey-Suzanne Ribeiro | 3 | 3 | 18 | 2 | 0.18 |
| 1867 | Guiying Qiu | 3 | 3 | 18 | 2 | 0.18 |
| 1868 | Jason Roberts | 3 | 3 | 18 | 2 | 0.18 |
| 1869 | Juan Yuan | 3 | 3 | 18 | 2 | 0.18 |
| 1870 | Lei Deng | 2 | 2 | 40 | 5 | 0.18 |
| 1871 | Jing Fang | 2 | 2 | 36 | 6 | 0.18 |
| 1872 | Xia Hao | 2 | 2 | 36 | 6 | 0.18 |
| 1873 | Maggie Faivre | 3 | 3 | 10 | 4 | 0.18 |
| 1874 | Cardboard Twenty-Five | 3 | 3 | 21 | 1 | 0.18 |
| 1875 | Chao Zheng | 3 | 3 | 21 | 1 | 0.18 |
| 1876 | Guiying Xia | 3 | 3 | 21 | 1 | 0.18 |
| 1877 | Yang Lai | 3 | 3 | 21 | 1 | 0.18 |
| 1878 | Paul Lewis | 2 | 2 | 32 | 7 | 0.18 |
| 1879 | Brandon Ramirez | 3 | 3 | 17 | 2 | 0.18 |
| 1880 | Ming Lai | 3 | 3 | 17 | 2 | 0.18 |
| 1881 | Xiulan Zhang | 3 | 3 | 17 | 2 | 0.18 |
| 1882 | James Jackson | 3 | 2 | 34 | 2 | 0.18 |
| 1883 | Gang Liu | 3 | 3 | 13 | 3 | 0.18 |
| 1884 | Guiying Chang | 3 | 3 | 20 | 1 | 0.18 |
| 1885 | Lei Qiao | 3 | 3 | 20 | 1 | 0.18 |
| 1886 | Min Wang | 3 | 3 | 20 | 1 | 0.18 |
| 1887 | Tao Gu | 3 | 3 | 20 | 1 | 0.18 |
| 1888 | Tao Long | 3 | 3 | 20 | 1 | 0.18 |
| 1889 | Wei Li | 3 | 3 | 20 | 1 | 0.18 |
| 1890 | Anthony King | 3 | 3 | 16 | 2 | 0.18 |
| 1891 | Echo Syntax | 3 | 3 | 16 | 2 | 0.18 |
| 1892 | Fang Zhu | 3 | 3 | 16 | 2 | 0.18 |
| 1893 | Ippazio Barcella | 3 | 3 | 16 | 2 | 0.18 |
| 1894 | Lei Zhong | 3 | 3 | 16 | 2 | 0.18 |
| 1895 | Nicole Scott | 3 | 3 | 16 | 2 | 0.18 |
| 1896 | Ping Dong | 3 | 3 | 16 | 2 | 0.18 |
| 1897 | Wei Qian | 3 | 3 | 16 | 2 | 0.18 |
| 1898 | Forjadura | 3 | 2 | 33 | 2 | 0.18 |
| 1899 | Tammy Chen | 3 | 2 | 33 | 2 | 0.18 |
| 1900 | Michelle Ellis | 2 | 2 | 27 | 8 | 0.18 |
| 1901 | Jolanda Salz | 3 | 3 | 12 | 3 | 0.18 |
| 1902 | Luna Spark | 3 | 3 | 12 | 3 | 0.18 |
| 1903 | Sayuri Sato | 3 | 3 | 12 | 3 | 0.18 |
| 1904 | Yang Deng | 3 | 3 | 12 | 3 | 0.18 |
| 1905 | David Schultz | 2 | 2 | 34 | 6 | 0.18 |
| 1906 | Jacqueline Dickson | 2 | 2 | 34 | 6 | 0.18 |
| 1907 | Jonathan Young | 2 | 2 | 34 | 6 | 0.18 |
| 1908 | Marianna Stefanik | 3 | 3 | 8 | 4 | 0.18 |
| 1909 | Fang Song | 3 | 3 | 19 | 1 | 0.18 |
| 1910 | Gang Qian | 3 | 3 | 19 | 1 | 0.18 |
| 1911 | Lei Xiao | 3 | 3 | 19 | 1 | 0.18 |
| 1912 | Na Cao | 3 | 3 | 19 | 1 | 0.18 |
| 1913 | Na Meng | 3 | 3 | 19 | 1 | 0.18 |
| 1914 | Tao Ding | 3 | 3 | 19 | 1 | 0.18 |
| 1915 | Xiulan Chang | 3 | 3 | 19 | 1 | 0.18 |
| 1916 | Jessica Lopez | 2 | 2 | 30 | 7 | 0.18 |
| 1917 | Jie Zhou | 2 | 2 | 30 | 7 | 0.18 |
| 1918 | Celestial Horizon | 3 | 3 | 15 | 2 | 0.18 |
| 1919 | Gang Zou | 3 | 3 | 15 | 2 | 0.18 |
| 1920 | Jing Zou | 3 | 3 | 15 | 2 | 0.18 |
| 1921 | Ping Qiao | 3 | 3 | 15 | 2 | 0.18 |
| 1922 | Ping Yu | 3 | 3 | 15 | 2 | 0.18 |
| 1923 | Ping Yuan | 3 | 3 | 15 | 2 | 0.18 |
| 1924 | Yan Lei | 3 | 3 | 15 | 2 | 0.18 |
| 1925 | Tao Qin | 2 | 2 | 37 | 5 | 0.18 |
| 1926 | Mark Martin | 1 | 1 | 48 | 11 | 0.18 |
| 1927 | Shawn Koch | 1 | 1 | 48 | 11 | 0.18 |
| 1928 | William Hansen | 1 | 1 | 48 | 11 | 0.18 |
| 1929 | Augustin Besnard-Imbert | 3 | 3 | 11 | 3 | 0.18 |
| 1930 | Diaspora Rising | 3 | 3 | 11 | 3 | 0.18 |
| 1931 | Dominique Perret | 3 | 3 | 11 | 3 | 0.18 |
| 1932 | Erdmute Hermann-Karge | 3 | 3 | 11 | 3 | 0.18 |
| 1933 | Gundi Barkholz | 3 | 3 | 11 | 3 | 0.18 |
| 1934 | Kevin Carney | 3 | 3 | 11 | 3 | 0.18 |
| 1935 | Lidia Szpyt | 3 | 3 | 11 | 3 | 0.18 |
| 1936 | Yan Zhao | 3 | 3 | 22 | 0 | 0.18 |
| 1937 | Kaylee Freeman | 2 | 2 | 22 | 9 | 0.18 |
| 1938 | Gang Huang | 2 | 2 | 33 | 6 | 0.18 |
| 1939 | David Stewart | 1 | 1 | 44 | 12 | 0.18 |
| 1940 | Juan Watkins | 1 | 1 | 44 | 12 | 0.18 |
| 1941 | Sheri Brooks | 1 | 1 | 44 | 12 | 0.18 |
| 1942 | Frau Marianna Wernecke | 3 | 3 | 18 | 1 | 0.18 |
| 1943 | Juan Chen | 3 | 3 | 18 | 1 | 0.18 |
| 1944 | Jun Qin | 3 | 3 | 18 | 1 | 0.18 |
| 1945 | Na Han | 3 | 3 | 18 | 1 | 0.18 |
| 1946 | Qiang Yu | 3 | 3 | 18 | 1 | 0.18 |
| 1947 | Guiying Fan | 3 | 3 | 14 | 2 | 0.18 |
| 1948 | Karl-Ludwig Kensy | 2 | 2 | 25 | 8 | 0.18 |
| 1949 | Tidal Reverie | 5 | 2 | 6 | 0 | 0.18 |
| 1950 | Jorge Hood | 2 | 2 | 36 | 5 | 0.18 |
| 1951 | Keith Hernandez | 2 | 2 | 36 | 5 | 0.18 |
| 1952 | Rossana Colletti | 2 | 2 | 36 | 5 | 0.18 |
| 1953 | Stephanie Silva | 2 | 2 | 36 | 5 | 0.18 |
| 1954 | Lisa Castillo | 3 | 3 | 10 | 3 | 0.18 |
| 1955 | Joseph Trujillo | 2 | 2 | 32 | 6 | 0.17 |
| 1956 | Juan Su | 3 | 3 | 17 | 1 | 0.17 |
| 1957 | Juan Zhou | 3 | 3 | 17 | 1 | 0.17 |
| 1958 | Xiuying Yu | 3 | 3 | 17 | 1 | 0.17 |
| 1959 | Lorenzo Morabito | 3 | 2 | 23 | 4 | 0.17 |
| 1960 | Cosmic Drift | 3 | 3 | 13 | 2 | 0.17 |
| 1961 | Julie Reynolds | 3 | 3 | 13 | 2 | 0.17 |
| 1962 | Jun Li | 3 | 3 | 13 | 2 | 0.17 |
| 1963 | Kathryn Ward | 3 | 3 | 13 | 2 | 0.17 |
| 1964 | Lei Peng | 3 | 3 | 13 | 2 | 0.17 |
| 1965 | Li Wei | 3 | 3 | 13 | 2 | 0.17 |
| 1966 | Tao Qiao | 3 | 3 | 13 | 2 | 0.17 |
| 1967 | Amber Allen | 2 | 2 | 24 | 8 | 0.17 |
| 1968 | Vperyod Siyanie! | 2 | 2 | 24 | 8 | 0.17 |
| 1969 | Yan Dai | 2 | 2 | 35 | 5 | 0.17 |
| 1970 | Jennifer Jackson | 1 | 1 | 46 | 11 | 0.17 |
| 1971 | Nancy Pierce | 1 | 1 | 46 | 11 | 0.17 |
| 1972 | Alex Halama | 3 | 3 | 9 | 3 | 0.17 |
| 1973 | Anatol Dietz | 3 | 3 | 9 | 3 | 0.17 |
| 1974 | Evelyn Hernandez | 3 | 3 | 9 | 3 | 0.17 |
| 1975 | Karina Bąbel | 3 | 3 | 9 | 3 | 0.17 |
| 1976 | Kathryn Sherman | 3 | 3 | 9 | 3 | 0.17 |
| 1977 | Whispered Strings | 3 | 3 | 9 | 3 | 0.17 |
| 1978 | Donna Ryan | 3 | 3 | 20 | 0 | 0.17 |
| 1979 | Charles Delahaye | 2 | 2 | 31 | 6 | 0.17 |
| 1980 | Juan Cheng | 3 | 3 | 16 | 1 | 0.17 |
| 1981 | Jun Long | 3 | 3 | 16 | 1 | 0.17 |
| 1982 | Na Jin | 3 | 3 | 16 | 1 | 0.17 |
| 1983 | Ping Jin | 3 | 3 | 16 | 1 | 0.17 |
| 1984 | Ryan Adams | 3 | 3 | 16 | 1 | 0.17 |
| 1985 | Wei Kang | 3 | 3 | 16 | 1 | 0.17 |
| 1986 | Xiuying Kang | 3 | 3 | 16 | 1 | 0.17 |
| 1987 | Xiuying Qian | 3 | 3 | 16 | 1 | 0.17 |
| 1988 | Adriana Figueroa | 1 | 1 | 49 | 10 | 0.17 |
| 1989 | Charles Hall | 1 | 1 | 49 | 10 | 0.17 |
| 1990 | James Mosley | 1 | 1 | 49 | 10 | 0.17 |
| 1991 | Thomas Dudley | 1 | 1 | 49 | 10 | 0.17 |
| 1992 | Justin Williams | 3 | 3 | 12 | 2 | 0.17 |
| 1993 | Ping Peng | 3 | 3 | 12 | 2 | 0.17 |
| 1994 | Rust & Reverie | 5 | 2 | 4 | 0 | 0.17 |
| 1995 | Selkie's Hollow | 5 | 2 | 4 | 0 | 0.17 |
| 1996 | Xiuying Sun | 2 | 2 | 34 | 5 | 0.17 |
| 1997 | Christopher Reed | 3 | 3 | 8 | 3 | 0.17 |
| 1998 | Jennifer Savage | 3 | 3 | 8 | 3 | 0.17 |
| 1999 | Jovens Sujos | 3 | 3 | 8 | 3 | 0.17 |
| 2000 | Rudolf Malý | 3 | 3 | 8 | 3 | 0.17 |
| 2001 | Stephen Bell | 3 | 3 | 8 | 3 | 0.17 |
| 2002 | Yong Bai | 3 | 3 | 8 | 3 | 0.17 |
| 2003 | Xia Chang | 3 | 3 | 19 | 0 | 0.17 |
| 2004 | Yang Duan | 3 | 2 | 25 | 3 | 0.17 |
| 2005 | Juan Gu | 2 | 2 | 30 | 6 | 0.17 |
| 2006 | Fang Chang | 3 | 3 | 15 | 1 | 0.17 |
| 2007 | Jing Wei | 3 | 3 | 15 | 1 | 0.17 |
| 2008 | Jun Feng | 3 | 3 | 15 | 1 | 0.17 |
| 2009 | Jun Hu | 3 | 3 | 15 | 1 | 0.17 |
| 2010 | Jun Peng | 3 | 3 | 15 | 1 | 0.17 |
| 2011 | Lei Xiong | 3 | 3 | 15 | 1 | 0.17 |
| 2012 | Min Wan | 3 | 3 | 15 | 1 | 0.17 |
| 2013 | Ming Zhong | 3 | 3 | 15 | 1 | 0.17 |
| 2014 | Nanami Yoshida | 3 | 3 | 15 | 1 | 0.17 |
| 2015 | Qiang Deng | 3 | 3 | 15 | 1 | 0.17 |
| 2016 | Tao Jia | 3 | 3 | 15 | 1 | 0.17 |
| 2017 | Xia Yang | 3 | 3 | 15 | 1 | 0.17 |
| 2018 | Xiuying Xia | 3 | 3 | 15 | 1 | 0.17 |
| 2019 | Yong Xia | 3 | 3 | 11 | 2 | 0.17 |
| 2020 | Violet Engines | 5 | 2 | 3 | 0 | 0.17 |
| 2021 | Emily Taylor | 2 | 2 | 33 | 5 | 0.17 |
| 2022 | Juan Zeng | 2 | 2 | 33 | 5 | 0.17 |
| 2023 | Na Yuan | 2 | 2 | 33 | 5 | 0.17 |
| 2024 | Tao Mao | 2 | 2 | 33 | 5 | 0.17 |
| 2025 | Jasmine Atkins | 3 | 3 | 7 | 3 | 0.17 |
| 2026 | Kazuya Aoki | 3 | 3 | 7 | 3 | 0.17 |
| 2027 | Antonietta Kreusel-Seip | 3 | 3 | 18 | 0 | 0.17 |
| 2028 | Xiuying Xu | 3 | 3 | 18 | 0 | 0.17 |
| 2029 | Kelli Williamson | 2 | 2 | 29 | 6 | 0.17 |
| 2030 | William Coleman | 2 | 2 | 29 | 6 | 0.17 |
| 2031 | Gabriel Malon | 3 | 3 | 3 | 4 | 0.17 |
| 2032 | Debra Martin | 3 | 2 | 9 | 7 | 0.17 |
| 2033 | Chao Lai | 3 | 3 | 14 | 1 | 0.17 |
| 2034 | Chao Liao | 3 | 3 | 14 | 1 | 0.17 |
| 2035 | Christine Jones | 3 | 3 | 14 | 1 | 0.17 |
| 2036 | Jing Kong | 3 | 3 | 14 | 1 | 0.17 |
| 2037 | Juan Fang | 3 | 3 | 14 | 1 | 0.17 |
| 2038 | Ping Guo | 3 | 3 | 14 | 1 | 0.17 |
| 2039 | Tao Li | 3 | 3 | 14 | 1 | 0.17 |
| 2040 | Tao Zheng | 3 | 3 | 14 | 1 | 0.17 |
| 2041 | David Rodriguez | 1 | 1 | 47 | 10 | 0.17 |
| 2042 | Rita Morrison | 1 | 1 | 47 | 10 | 0.17 |
| 2043 | Bhamini Saini | 3 | 3 | 10 | 2 | 0.17 |
| 2044 | Fabian Dłubak | 3 | 3 | 10 | 2 | 0.17 |
| 2045 | Lei Gu | 3 | 3 | 10 | 2 | 0.17 |
| 2046 | Leslie Mathis | 3 | 3 | 10 | 2 | 0.17 |
| 2047 | Patricia Hardy | 3 | 3 | 10 | 2 | 0.17 |
| 2048 | Phantom Syntax | 3 | 3 | 10 | 2 | 0.17 |
| 2049 | Turbo Kill | 5 | 2 | 2 | 0 | 0.17 |
| 2050 | Ming Hao | 2 | 2 | 32 | 5 | 0.17 |
| 2051 | Fang Xue | 3 | 3 | 6 | 3 | 0.17 |
| 2052 | Logan Rogers | 3 | 3 | 6 | 3 | 0.17 |
| 2053 | Megan Gilmore | 3 | 3 | 6 | 3 | 0.17 |
| 2054 | Lucas Potter | 3 | 2 | 12 | 6 | 0.17 |
| 2055 | Stormens Sång | 3 | 2 | 12 | 6 | 0.17 |
| 2056 | Jing Han | 3 | 3 | 17 | 0 | 0.17 |
| 2057 | Jun Yao | 3 | 3 | 17 | 0 | 0.17 |
| 2058 | Qiang Mao | 3 | 3 | 17 | 0 | 0.17 |
| 2059 | Yang Lei | 3 | 3 | 17 | 0 | 0.17 |
| 2060 | Peggy Krebs | 2 | 2 | 28 | 6 | 0.17 |
| 2061 | Na Zeng | 3 | 3 | 13 | 1 | 0.17 |
| 2062 | Paul Castro | 3 | 3 | 13 | 1 | 0.17 |
| 2063 | Tao Yan | 3 | 3 | 13 | 1 | 0.17 |
| 2064 | Wei Zhu | 3 | 3 | 13 | 1 | 0.17 |
| 2065 | Xiuying Zhou | 3 | 3 | 13 | 1 | 0.17 |
| 2066 | Loro | 3 | 2 | 19 | 4 | 0.17 |
| 2067 | Elizabeth Chase | 2 | 2 | 35 | 4 | 0.17 |
| 2068 | Heather Lutz | 3 | 3 | 9 | 2 | 0.17 |
| 2069 | Nirvaan Barman | 3 | 3 | 9 | 2 | 0.17 |
| 2070 | Anna Shaw | 2 | 2 | 31 | 5 | 0.17 |
| 2071 | Deborah Rogers | 2 | 2 | 31 | 5 | 0.17 |
| 2072 | Kristin Miranda | 2 | 2 | 31 | 5 | 0.17 |
| 2073 | Obsidian Harmony | 2 | 2 | 31 | 5 | 0.17 |
| 2074 | Ping Chen | 2 | 2 | 31 | 5 | 0.17 |
| 2075 | Yan Deng | 2 | 2 | 31 | 5 | 0.17 |
| 2076 | Jacqueline Fields | 3 | 3 | 5 | 3 | 0.17 |
| 2077 | Inès Collet | 3 | 3 | 16 | 0 | 0.17 |
| 2078 | Juan Xia | 3 | 3 | 16 | 0 | 0.17 |
| 2079 | Wei Long | 3 | 3 | 16 | 0 | 0.17 |
| 2080 | Joshua Oneill | 2 | 2 | 27 | 6 | 0.17 |
| 2081 | Ming Qian | 2 | 2 | 27 | 6 | 0.17 |
| 2082 | The Cedar Lane Collective | 2 | 2 | 27 | 6 | 0.17 |
| 2083 | Chao Guo | 3 | 3 | 12 | 1 | 0.17 |
| 2084 | Judith Hunter | 3 | 3 | 12 | 1 | 0.17 |
| 2085 | Kenneth Crosby | 3 | 3 | 12 | 1 | 0.17 |
| 2086 | Paula Wilson | 3 | 3 | 12 | 1 | 0.17 |
| 2087 | Phantom Resonance | 3 | 3 | 12 | 1 | 0.17 |
| 2088 | Rachel Wilson | 3 | 3 | 12 | 1 | 0.17 |
| 2089 | Steven Branch | 3 | 3 | 12 | 1 | 0.17 |
| 2090 | Matthäus Ladeck | 3 | 2 | 18 | 4 | 0.17 |
| 2091 | Ida Kenig | 2 | 2 | 12 | 10 | 0.17 |
| 2092 | Darlene Galloway | 2 | 2 | 34 | 4 | 0.17 |
| 2093 | Melanie Fisher | 2 | 2 | 34 | 4 | 0.17 |
| 2094 | Bianca Peano | 2 | 1 | 40 | 7 | 0.17 |
| 2095 | Yang Kang | 1 | 1 | 45 | 10 | 0.17 |
| 2096 | Antoine Barthelemy | 3 | 3 | 8 | 2 | 0.17 |
| 2097 | Fixx'd | 3 | 3 | 8 | 2 | 0.17 |
| 2098 | Melina Tebaldi | 3 | 3 | 8 | 2 | 0.17 |
| 2099 | Richard Gutierrez | 3 | 3 | 8 | 2 | 0.17 |
| 2100 | Zara Trivedi | 3 | 3 | 8 | 2 | 0.17 |
| 2101 | Andrea Miller | 2 | 2 | 19 | 8 | 0.17 |
| 2102 | Holly Valenzuela | 2 | 2 | 30 | 5 | 0.17 |
| 2103 | Edit Hethur | 3 | 3 | 4 | 3 | 0.16 |
| 2104 | Janna Jäkel | 3 | 3 | 4 | 3 | 0.16 |
| 2105 | Kelly Jones | 3 | 3 | 4 | 3 | 0.16 |
| 2106 | Krista Wallace | 3 | 3 | 4 | 3 | 0.16 |
| 2107 | Margit Sölzer | 3 | 3 | 4 | 3 | 0.16 |
| 2108 | Parallel Static | 3 | 3 | 4 | 3 | 0.16 |
| 2109 | Paula Mercado | 3 | 3 | 4 | 3 | 0.16 |
| 2110 | Restless Verse | 3 | 3 | 4 | 3 | 0.16 |
| 2111 | Scott Richmond | 3 | 3 | 4 | 3 | 0.16 |
| 2112 | Herr Arno Ebert | 1 | 1 | 52 | 8 | 0.16 |
| 2113 | Jeffrey Roman | 1 | 1 | 52 | 8 | 0.16 |
| 2114 | Marlene Scholtz | 1 | 1 | 52 | 8 | 0.16 |
| 2115 | Patrick Grein Groth | 1 | 1 | 52 | 8 | 0.16 |
| 2116 | Veronika Haering | 1 | 1 | 52 | 8 | 0.16 |
| 2117 | Willibert Ebert | 1 | 1 | 52 | 8 | 0.16 |
| 2118 | Chao Xiong | 3 | 3 | 15 | 0 | 0.16 |
| 2119 | Ming Zou | 3 | 3 | 15 | 0 | 0.16 |
| 2120 | Nicholas Davis | 2 | 2 | 26 | 6 | 0.16 |
| 2121 | Anneliese Bolnbach | 3 | 3 | 11 | 1 | 0.16 |
| 2122 | Gang Duan | 3 | 3 | 11 | 1 | 0.16 |
| 2123 | Kevin Wong | 3 | 3 | 11 | 1 | 0.16 |
| 2124 | Michelle Byrd | 3 | 3 | 11 | 1 | 0.16 |
| 2125 | Valhalla's Fury | 3 | 3 | 11 | 1 | 0.16 |
| 2126 | Frederic Margraf | 3 | 2 | 17 | 4 | 0.16 |
| 2127 | Ming Tan | 2 | 2 | 22 | 7 | 0.16 |
| 2128 | Wei Wen | 2 | 2 | 33 | 4 | 0.16 |
| 2129 | Yong Han | 2 | 2 | 33 | 4 | 0.16 |
| 2130 | Amber Gibson | 3 | 3 | 7 | 2 | 0.16 |
| 2131 | David Miller | 3 | 3 | 7 | 2 | 0.16 |
| 2132 | Francisco Krein-Möchlichen | 3 | 3 | 7 | 2 | 0.16 |
| 2133 | Lawrence Cooper | 3 | 3 | 7 | 2 | 0.16 |
| 2134 | Mai Sato | 3 | 3 | 7 | 2 | 0.16 |
| 2135 | Margaret Martin | 3 | 3 | 7 | 2 | 0.16 |
| 2136 | Ming Bai | 3 | 3 | 7 | 2 | 0.16 |
| 2137 | Ping Mao | 3 | 3 | 7 | 2 | 0.16 |
| 2138 | Urban Decay Theorem | 3 | 3 | 7 | 2 | 0.16 |
| 2139 | Brittany Kelly | 2 | 2 | 29 | 5 | 0.16 |
| 2140 | Christopher Roberts | 2 | 2 | 29 | 5 | 0.16 |
| 2141 | Fang Han | 3 | 3 | 14 | 0 | 0.16 |
| 2142 | Friedo Dobes | 3 | 3 | 14 | 0 | 0.16 |
| 2143 | Ming Shao | 3 | 3 | 14 | 0 | 0.16 |
| 2144 | Ming Yuan | 3 | 3 | 14 | 0 | 0.16 |
| 2145 | Tao Pan | 3 | 3 | 14 | 0 | 0.16 |
| 2146 | Lei Kang | 3 | 2 | 20 | 3 | 0.16 |
| 2147 | Nicole Robinson | 2 | 2 | 14 | 9 | 0.16 |
| 2148 | Brandon Mays | 2 | 2 | 25 | 6 | 0.16 |
| 2149 | Jessica Macdonald | 2 | 2 | 25 | 6 | 0.16 |
| 2150 | Crimson Harvest | 3 | 3 | 10 | 1 | 0.16 |
| 2151 | Fang Dai | 3 | 3 | 10 | 1 | 0.16 |
| 2152 | Jun He | 3 | 3 | 10 | 1 | 0.16 |
| 2153 | Li Shi | 3 | 3 | 10 | 1 | 0.16 |
| 2154 | Min Fan | 3 | 3 | 10 | 1 | 0.16 |
| 2155 | Richard Johnson | 3 | 3 | 10 | 1 | 0.16 |
| 2156 | Min Zhang | 2 | 2 | 32 | 4 | 0.16 |
| 2157 | Antonius Faust | 3 | 3 | 6 | 2 | 0.16 |
| 2158 | Carlo Mazzacurati | 3 | 3 | 6 | 2 | 0.16 |
| 2159 | Jeremy Li | 3 | 3 | 6 | 2 | 0.16 |
| 2160 | Joseph Burgess | 3 | 3 | 6 | 2 | 0.16 |
| 2161 | Misfit Bistro | 3 | 3 | 6 | 2 | 0.16 |
| 2162 | Rosaria Pedersoli | 3 | 3 | 6 | 2 | 0.16 |
| 2163 | Stephanie Garcia | 3 | 3 | 6 | 2 | 0.16 |
| 2164 | Jacob Harris | 3 | 2 | 12 | 5 | 0.16 |
| 2165 | Brandi Bates | 2 | 2 | 28 | 5 | 0.16 |
| 2166 | Fang Tian | 3 | 3 | 13 | 0 | 0.16 |
| 2167 | Juan Mao | 3 | 3 | 13 | 0 | 0.16 |
| 2168 | Lei Qian | 3 | 3 | 13 | 0 | 0.16 |
| 2169 | Ping Gu | 3 | 3 | 13 | 0 | 0.16 |
| 2170 | Barbara Mckee | 3 | 3 | 9 | 1 | 0.16 |
| 2171 | Elizabeth Johnson | 3 | 3 | 9 | 1 | 0.16 |
| 2172 | Erin Welch | 3 | 3 | 9 | 1 | 0.16 |
| 2173 | Immortal Spark | 3 | 3 | 9 | 1 | 0.16 |
| 2174 | Jie Liang | 3 | 3 | 9 | 1 | 0.16 |
| 2175 | Jing Luo | 3 | 3 | 9 | 1 | 0.16 |
| 2176 | Regina Bruce | 3 | 3 | 9 | 1 | 0.16 |
| 2177 | Min Yan | 2 | 2 | 31 | 4 | 0.16 |
| 2178 | Yang Wen | 2 | 2 | 31 | 4 | 0.16 |
| 2179 | Artisans of Rhythm | 3 | 3 | 5 | 2 | 0.16 |
| 2180 | Christopher Thomas | 3 | 3 | 5 | 2 | 0.16 |
| 2181 | Jessica Harvey | 3 | 3 | 5 | 2 | 0.16 |
| 2182 | Joann Johnson | 3 | 3 | 5 | 2 | 0.16 |
| 2183 | Laure du Hebert | 3 | 3 | 5 | 2 | 0.16 |
| 2184 | Michael Maddox | 3 | 3 | 5 | 2 | 0.16 |
| 2185 | Nathalie Legrand | 3 | 3 | 5 | 2 | 0.16 |
| 2186 | Pavlína Macháčková | 3 | 3 | 5 | 2 | 0.16 |
| 2187 | Pompeo Turchi | 3 | 3 | 5 | 2 | 0.16 |
| 2188 | Radiant Siblings | 3 | 3 | 5 | 2 | 0.16 |
| 2189 | Rati Deo | 3 | 3 | 5 | 2 | 0.16 |
| 2190 | Rebel Scream | 3 | 3 | 5 | 2 | 0.16 |
| 2191 | Sarah Gardner | 3 | 3 | 5 | 2 | 0.16 |
| 2192 | Timothy Bray | 3 | 3 | 5 | 2 | 0.16 |
| 2193 | David Johnson | 3 | 2 | 22 | 2 | 0.16 |
| 2194 | Angelina Ortmann | 2 | 2 | 27 | 5 | 0.16 |
| 2195 | Janet Margraf | 2 | 2 | 27 | 5 | 0.16 |
| 2196 | Juan Kong | 2 | 2 | 27 | 5 | 0.16 |
| 2197 | Danielle Gray | 3 | 3 | 12 | 0 | 0.16 |
| 2198 | Jun Gao | 3 | 3 | 12 | 0 | 0.16 |
| 2199 | Laurent Breton | 3 | 3 | 12 | 0 | 0.16 |
| 2200 | Lisa Hart | 3 | 3 | 12 | 0 | 0.16 |
| 2201 | Qiang Huang | 3 | 3 | 12 | 0 | 0.16 |
| 2202 | Astrid Gomes | 3 | 2 | 18 | 3 | 0.16 |
| 2203 | Li Chang | 3 | 2 | 18 | 3 | 0.16 |
| 2204 | Cesare Cicilia | 2 | 2 | 23 | 6 | 0.16 |
| 2205 | Yong Ren | 2 | 2 | 23 | 6 | 0.16 |
| 2206 | Diane Dunn | 1 | 1 | 45 | 9 | 0.16 |
| 2207 | Na Liang | 1 | 1 | 45 | 9 | 0.16 |
| 2208 | Gabor Salz | 3 | 3 | 8 | 1 | 0.16 |
| 2209 | Francesca Krebs | 2 | 2 | 19 | 7 | 0.16 |
| 2210 | Ronnie Cook | 2 | 2 | 19 | 7 | 0.16 |
| 2211 | Min Liu | 2 | 2 | 30 | 4 | 0.16 |
| 2212 | Amy Tate | 3 | 3 | 4 | 2 | 0.16 |
| 2213 | Antoine Perrot-Léger | 3 | 3 | 4 | 2 | 0.16 |
| 2214 | Charlotte Lefèvre | 3 | 3 | 4 | 2 | 0.16 |
| 2215 | Christine Bonnin-Morel | 3 | 3 | 4 | 2 | 0.16 |
| 2216 | Hridaan Kaur | 3 | 3 | 4 | 2 | 0.16 |
| 2217 | Matthieu Le Roux | 3 | 3 | 4 | 2 | 0.16 |
| 2218 | Operatic Insurgence | 3 | 3 | 4 | 2 | 0.16 |
| 2219 | Phantom Sync | 3 | 3 | 4 | 2 | 0.16 |
| 2220 | Rohan Shanker | 3 | 3 | 4 | 2 | 0.16 |
| 2221 | Rémy Denis de Duhamel | 3 | 3 | 4 | 2 | 0.16 |
| 2222 | Spectral Junk | 3 | 3 | 4 | 2 | 0.16 |
| 2223 | Talvikierros | 3 | 3 | 4 | 2 | 0.16 |
| 2224 | The Three Drafts | 3 | 3 | 4 | 2 | 0.16 |
| 2225 | Berend Suijker-Tirie | 2 | 2 | 26 | 5 | 0.16 |
| 2226 | Yang Yuan | 2 | 2 | 26 | 5 | 0.16 |
| 2227 | Heinz-Joachim Renner | 1 | 1 | 37 | 11 | 0.16 |
| 2228 | Chao Gao | 3 | 3 | 11 | 0 | 0.16 |
| 2229 | Fang Yuan | 3 | 3 | 11 | 0 | 0.16 |
| 2230 | Guiying He | 3 | 3 | 11 | 0 | 0.16 |
| 2231 | Jing Gong | 3 | 3 | 11 | 0 | 0.16 |
| 2232 | Ming Tian | 3 | 3 | 11 | 0 | 0.16 |
| 2233 | Ping Su | 3 | 3 | 11 | 0 | 0.16 |
| 2234 | Wei Qiu | 3 | 3 | 11 | 0 | 0.16 |
| 2235 | Xia Han | 3 | 3 | 11 | 0 | 0.16 |
| 2236 | Guiying Lai | 3 | 3 | 7 | 1 | 0.16 |
| 2237 | Juan Ma | 3 | 3 | 7 | 1 | 0.16 |
| 2238 | Juan Ye | 3 | 3 | 7 | 1 | 0.16 |
| 2239 | Michel Meyer | 3 | 3 | 7 | 1 | 0.16 |
| 2240 | Undetected | 3 | 3 | 7 | 1 | 0.16 |
| 2241 | Xiuying Liang | 3 | 3 | 7 | 1 | 0.16 |
| 2242 | Li Du | 2 | 2 | 29 | 4 | 0.16 |
| 2243 | Subtle Noise | 2 | 2 | 29 | 4 | 0.16 |
| 2244 | Inaaya Bhatia | 3 | 3 | 3 | 2 | 0.16 |
| 2245 | Kendra Green | 3 | 3 | 3 | 2 | 0.16 |
| 2246 | Nehmat Kanda | 3 | 3 | 3 | 2 | 0.16 |
| 2247 | Paula Bonbach | 3 | 3 | 3 | 2 | 0.16 |
| 2248 | Quantum Sonic Architects | 3 | 3 | 3 | 2 | 0.16 |
| 2249 | Robert Woods | 3 | 3 | 3 | 2 | 0.16 |
| 2250 | Split Persona | 3 | 3 | 3 | 2 | 0.16 |
| 2251 | Wieslaw Wulf | 3 | 3 | 3 | 2 | 0.16 |
| 2252 | Qiang Ding | 3 | 2 | 20 | 2 | 0.16 |
| 2253 | Ping Wen | 2 | 2 | 25 | 5 | 0.16 |
| 2254 | Angela Gonzalez | 1 | 1 | 36 | 11 | 0.16 |
| 2255 | Nicole Gonzalez | 1 | 1 | 36 | 11 | 0.16 |
| 2256 | Gang Xiang | 3 | 3 | 10 | 0 | 0.16 |
| 2257 | Guiying Cui | 3 | 3 | 10 | 0 | 0.16 |
| 2258 | Wei Jia | 3 | 3 | 10 | 0 | 0.16 |
| 2259 | Thibault Hardy | 2 | 2 | 21 | 6 | 0.16 |
| 2260 | Brandon Santos | 2 | 1 | 27 | 9 | 0.16 |
| 2261 | Brian Palmer | 2 | 2 | 32 | 3 | 0.16 |
| 2262 | Brittany Bush | 2 | 2 | 32 | 3 | 0.16 |
| 2263 | William Fuentes | 2 | 2 | 32 | 3 | 0.16 |
| 2264 | Bryan Garcia | 3 | 3 | 6 | 1 | 0.16 |
| 2265 | Colette-Jeannine Lemaître | 3 | 3 | 6 | 1 | 0.16 |
| 2266 | Crystal Cruz | 3 | 3 | 6 | 1 | 0.16 |
| 2267 | Electric Novella | 3 | 3 | 6 | 1 | 0.16 |
| 2268 | Emmanuel de Blot | 3 | 3 | 6 | 1 | 0.16 |
| 2269 | Kimberly Roberts | 3 | 3 | 6 | 1 | 0.16 |
| 2270 | Meik Plath | 3 | 3 | 6 | 1 | 0.16 |
| 2271 | Raymond Chartier | 3 | 3 | 6 | 1 | 0.16 |
| 2272 | Simone Parent | 3 | 3 | 6 | 1 | 0.16 |
| 2273 | Triassic Collective | 3 | 3 | 6 | 1 | 0.16 |
| 2274 | Valerie Brown | 3 | 3 | 6 | 1 | 0.16 |
| 2275 | Gang Dai | 3 | 2 | 23 | 1 | 0.16 |
| 2276 | Fang Qiu | 2 | 2 | 28 | 4 | 0.16 |
| 2277 | Jun Zhu | 2 | 2 | 28 | 4 | 0.16 |
| 2278 | Min Xue | 2 | 2 | 28 | 4 | 0.16 |
| 2279 | Tony Rhodes | 2 | 2 | 28 | 4 | 0.16 |
| 2280 | Michael Ross | 3 | 3 | 2 | 2 | 0.16 |
| 2281 | Wayne Malone | 3 | 2 | 19 | 2 | 0.16 |
| 2282 | Guiying Tan | 2 | 2 | 24 | 5 | 0.16 |
| 2283 | Gang Lin | 3 | 3 | 9 | 0 | 0.15 |
| 2284 | Juan Peng | 3 | 3 | 9 | 0 | 0.15 |
| 2285 | Vincent Morrison | 2 | 2 | 20 | 6 | 0.15 |
| 2286 | Capucine Pasquier | 3 | 3 | 5 | 1 | 0.15 |
| 2287 | Li Fu | 3 | 3 | 5 | 1 | 0.15 |
| 2288 | Ludovico Mondadori | 3 | 3 | 5 | 1 | 0.15 |
| 2289 | Martino Toninelli | 3 | 3 | 5 | 1 | 0.15 |
| 2290 | Yong Zou | 3 | 2 | 22 | 1 | 0.15 |
| 2291 | Kathleen Cunningham | 2 | 2 | 16 | 7 | 0.15 |
| 2292 | April Johnson | 2 | 2 | 27 | 4 | 0.15 |
| 2293 | Lara Wohlgemut | 2 | 2 | 27 | 4 | 0.15 |
| 2294 | Li Zou | 2 | 2 | 27 | 4 | 0.15 |
| 2295 | Operatic Pulse | 2 | 2 | 27 | 4 | 0.15 |
| 2296 | Kenichi Kobayashi | 3 | 3 | 1 | 2 | 0.15 |
| 2297 | Kari Sutton | 1 | 1 | 45 | 8 | 0.15 |
| 2298 | Jade Thompson | 3 | 3 | 8 | 0 | 0.15 |
| 2299 | Lila "Lilly" Hartman | 3 | 3 | 8 | 0 | 0.15 |
| 2300 | Adèle Bonneau | 2 | 2 | 19 | 6 | 0.15 |
| 2301 | Leah Anderson | 2 | 2 | 19 | 6 | 0.15 |
| 2302 | Wei Qiao | 2 | 2 | 30 | 3 | 0.15 |
| 2303 | Corinne du Bazin | 3 | 3 | 4 | 1 | 0.15 |
| 2304 | Dawn Ramsey | 3 | 3 | 4 | 1 | 0.15 |
| 2305 | Double Chance | 3 | 3 | 4 | 1 | 0.15 |
| 2306 | Jacob Boyd | 3 | 3 | 4 | 1 | 0.15 |
| 2307 | Marianne Sanchez-Hebert | 3 | 3 | 4 | 1 | 0.15 |
| 2308 | Sarah James | 3 | 3 | 4 | 1 | 0.15 |
| 2309 | Susan Mcclain | 3 | 3 | 4 | 1 | 0.15 |
| 2310 | Tracey Jordan | 3 | 3 | 4 | 1 | 0.15 |
| 2311 | Adrien Gérard | 3 | 2 | 10 | 4 | 0.15 |
| 2312 | Michel Fournier-Robert | 3 | 2 | 10 | 4 | 0.15 |
| 2313 | Guiying Gong | 3 | 2 | 21 | 1 | 0.15 |
| 2314 | Guiying Xie | 3 | 2 | 17 | 2 | 0.15 |
| 2315 | Ming Wang | 3 | 2 | 17 | 2 | 0.15 |
| 2316 | Mikołaj Rosłoń | 3 | 3 | 7 | 0 | 0.15 |
| 2317 | Na Hou | 3 | 3 | 7 | 0 | 0.15 |
| 2318 | Chao Zhang | 2 | 2 | 29 | 3 | 0.15 |
| 2319 | Amanda Hill | 3 | 3 | 3 | 1 | 0.15 |
| 2320 | Joseph Vincent | 3 | 3 | 3 | 1 | 0.15 |
| 2321 | Kaja Juroszek | 3 | 3 | 3 | 1 | 0.15 |
| 2322 | Karol Jereczek | 3 | 3 | 3 | 1 | 0.15 |
| 2323 | Lueur | 3 | 3 | 3 | 1 | 0.15 |
| 2324 | Timothy Burke | 3 | 3 | 3 | 1 | 0.15 |
| 2325 | Jonathan Wade | 3 | 2 | 16 | 2 | 0.15 |
| 2326 | Christopher Rosales | 2 | 2 | 21 | 5 | 0.15 |
| 2327 | Kuno Grein Groth | 2 | 2 | 21 | 5 | 0.15 |
| 2328 | Tara Jennings | 2 | 2 | 21 | 5 | 0.15 |
| 2329 | Wei Xia | 2 | 2 | 21 | 5 | 0.15 |
| 2330 | Dawn Nelson | 2 | 2 | 32 | 2 | 0.15 |
| 2331 | Arlo Sterling | 3 | 3 | 6 | 0 | 0.15 |
| 2332 | Cassian Rae | 3 | 3 | 6 | 0 | 0.15 |
| 2333 | Elara May | 3 | 3 | 6 | 0 | 0.15 |
| 2334 | Eva-Marie Seidel-Otto | 3 | 3 | 6 | 0 | 0.15 |
| 2335 | Lyra Blaze | 3 | 3 | 6 | 0 | 0.15 |
| 2336 | Orion Cruz | 3 | 3 | 6 | 0 | 0.15 |
| 2337 | William Roux | 3 | 1 | 29 | 3 | 0.15 |
| 2338 | Jing Hou | 2 | 2 | 28 | 3 | 0.15 |
| 2339 | Michael Richard | 2 | 2 | 28 | 3 | 0.15 |
| 2340 | Ryan Palmer | 2 | 2 | 28 | 3 | 0.15 |
| 2341 | Gioacchino Gargallo | 2 | 1 | 34 | 6 | 0.15 |
| 2342 | Randolf Fiebig | 2 | 1 | 34 | 6 | 0.15 |
| 2343 | Dorothée Rousset | 1 | 1 | 39 | 9 | 0.15 |
| 2344 | Amy White | 3 | 3 | 2 | 1 | 0.15 |
| 2345 | Eric Lewis | 3 | 3 | 2 | 1 | 0.15 |
| 2346 | William Jones | 3 | 3 | 2 | 1 | 0.15 |
| 2347 | Marija Lehmann | 2 | 2 | 13 | 7 | 0.15 |
| 2348 | John Hernandez | 2 | 2 | 24 | 4 | 0.15 |
| 2349 | Juan Shen | 2 | 2 | 24 | 4 | 0.15 |
| 2350 | Kimberly Ross | 2 | 2 | 24 | 4 | 0.15 |
| 2351 | Stacy Henderson | 2 | 2 | 24 | 4 | 0.15 |
| 2352 | Matthew Miller | 1 | 1 | 24 | 13 | 0.15 |
| 2353 | Gang Xia | 3 | 2 | 15 | 2 | 0.15 |
| 2354 | Daniel Rogers | 2 | 2 | 31 | 2 | 0.15 |
| 2355 | Caleb Foster | 3 | 3 | 5 | 0 | 0.15 |
| 2356 | Eleanor Wren | 3 | 3 | 5 | 0 | 0.15 |
| 2357 | Kai Reynolds | 3 | 3 | 5 | 0 | 0.15 |
| 2358 | Michael Smith | 3 | 3 | 5 | 0 | 0.15 |
| 2359 | Moral Friction | 3 | 3 | 5 | 0 | 0.15 |
| 2360 | Gunther Hendriks | 2 | 2 | 16 | 6 | 0.15 |
| 2361 | Gang Yao | 2 | 2 | 27 | 3 | 0.15 |
| 2362 | Guiying Duan | 2 | 2 | 27 | 3 | 0.15 |
| 2363 | Lotte Arens | 2 | 2 | 27 | 3 | 0.15 |
| 2364 | Ming Kong | 3 | 2 | 18 | 1 | 0.15 |
| 2365 | Xia Ma | 3 | 2 | 18 | 1 | 0.15 |
| 2366 | Erin Shah | 2 | 2 | 23 | 4 | 0.15 |
| 2367 | James Moore | 2 | 2 | 23 | 4 | 0.15 |
| 2368 | Li Yao | 2 | 2 | 23 | 4 | 0.15 |
| 2369 | Karol Klęczar | 2 | 2 | 8 | 8 | 0.15 |
| 2370 | Robin Russell | 2 | 2 | 19 | 5 | 0.15 |
| 2371 | Theresa Pena | 1 | 1 | 19 | 14 | 0.15 |
| 2372 | William Mcfarland | 1 | 1 | 19 | 14 | 0.15 |
| 2373 | The Wave Riders | 4 | 2 | 5 | 0 | 0.15 |
| 2374 | Audrey Johnson | 1 | 1 | 41 | 8 | 0.15 |
| 2375 | Dhruv Mall | 1 | 1 | 41 | 8 | 0.15 |
| 2376 | Áurea Escobar-Jara | 1 | 1 | 41 | 8 | 0.15 |
| 2377 | Ivy Steele | 3 | 3 | 4 | 0 | 0.15 |
| 2378 | Mikayla Cook | 3 | 3 | 4 | 0 | 0.15 |
| 2379 | Nate Wild | 3 | 3 | 4 | 0 | 0.15 |
| 2380 | Scarlett Moon | 3 | 3 | 4 | 0 | 0.15 |
| 2381 | Kristina Gonzales | 2 | 2 | 15 | 6 | 0.15 |
| 2382 | Danielle Luna | 2 | 1 | 21 | 9 | 0.15 |
| 2383 | John Pitts | 2 | 2 | 26 | 3 | 0.15 |
| 2384 | Xia Ye | 3 | 2 | 17 | 1 | 0.15 |
| 2385 | Juan Bai | 2 | 2 | 22 | 4 | 0.15 |
| 2386 | Nocturnal Drifters | 2 | 2 | 22 | 4 | 0.15 |
| 2387 | Xiulan Fang | 2 | 2 | 22 | 4 | 0.15 |
| 2388 | Amber Murray | 1 | 1 | 44 | 7 | 0.15 |
| 2389 | Autumn Moore | 1 | 1 | 44 | 7 | 0.15 |
| 2390 | Gabrielle Wright | 1 | 1 | 44 | 7 | 0.15 |
| 2391 | Kimberly Zimmerman | 1 | 1 | 44 | 7 | 0.15 |
| 2392 | Melissa Brown | 1 | 1 | 44 | 7 | 0.15 |
| 2393 | Stacy Kennedy | 1 | 1 | 44 | 7 | 0.15 |
| 2394 | Tina Jackson | 1 | 1 | 44 | 7 | 0.15 |
| 2395 | Liquid Prism | 3 | 2 | 13 | 2 | 0.15 |
| 2396 | Echoes of Eternity | 3 | 3 | 3 | 0 | 0.14 |
| 2397 | Sandra Green | 3 | 3 | 3 | 0 | 0.14 |
| 2398 | Tamara Solis | 3 | 3 | 3 | 0 | 0.14 |
| 2399 | Gregg Fuentes | 3 | 2 | 9 | 3 | 0.14 |
| 2400 | Mineral Breath Asphalt | 3 | 2 | 9 | 3 | 0.14 |
| 2401 | Jordan Collins | 2 | 2 | 14 | 6 | 0.14 |
| 2402 | Chao Gong | 2 | 2 | 25 | 3 | 0.14 |
| 2403 | Fang Qin | 2 | 2 | 25 | 3 | 0.14 |
| 2404 | Xiuying Luo | 2 | 2 | 25 | 3 | 0.14 |
| 2405 | Yang Xue | 2 | 2 | 25 | 3 | 0.14 |
| 2406 | Ellen Riley | 1 | 1 | 25 | 12 | 0.14 |
| 2407 | Silja Jacob | 1 | 1 | 25 | 12 | 0.14 |
| 2408 | Yang Yan | 3 | 2 | 16 | 1 | 0.14 |
| 2409 | Dean Stevens | 2 | 2 | 21 | 4 | 0.14 |
| 2410 | Ming Ye | 2 | 2 | 21 | 4 | 0.14 |
| 2411 | Stormheart | 2 | 2 | 21 | 4 | 0.14 |
| 2412 | Xiulan Zhu | 2 | 2 | 21 | 4 | 0.14 |
| 2413 | Xia Zheng | 2 | 2 | 17 | 5 | 0.14 |
| 2414 | Siren's Call | 4 | 2 | 3 | 0 | 0.14 |
| 2415 | Michael Bell | 1 | 1 | 39 | 8 | 0.14 |
| 2416 | Richard Hill | 1 | 1 | 39 | 8 | 0.14 |
| 2417 | Li Huang | 3 | 2 | 19 | 0 | 0.14 |
| 2418 | Ashley Cabrera | 2 | 2 | 13 | 6 | 0.14 |
| 2419 | Jazzy Wanderers | 2 | 2 | 13 | 6 | 0.14 |
| 2420 | Terrance Parker PhD | 2 | 2 | 24 | 3 | 0.14 |
| 2421 | Victoria Pierce | 2 | 2 | 24 | 3 | 0.14 |
| 2422 | Wei Sun | 2 | 2 | 24 | 3 | 0.14 |
| 2423 | Xiuying Chang | 2 | 2 | 24 | 3 | 0.14 |
| 2424 | Alexandra Levy | 2 | 2 | 20 | 4 | 0.14 |
| 2425 | Jing Xie | 2 | 2 | 20 | 4 | 0.14 |
| 2426 | Lauretta Tresoldi | 2 | 2 | 20 | 4 | 0.14 |
| 2427 | Michael Dean | 2 | 2 | 20 | 4 | 0.14 |
| 2428 | Adam Wallace | 1 | 1 | 31 | 10 | 0.14 |
| 2429 | Jennifer Stephens | 1 | 1 | 31 | 10 | 0.14 |
| 2430 | Yong Qiu | 3 | 1 | 28 | 2 | 0.14 |
| 2431 | Amanda Brock | 2 | 2 | 16 | 5 | 0.14 |
| 2432 | David Hernandez | 2 | 2 | 16 | 5 | 0.14 |
| 2433 | Karl-Heinz Bruder | 2 | 2 | 16 | 5 | 0.14 |
| 2434 | William Cruz | 2 | 2 | 16 | 5 | 0.14 |
| 2435 | Gundel Klapp | 2 | 2 | 27 | 2 | 0.14 |
| 2436 | Na Cai | 2 | 2 | 27 | 2 | 0.14 |
| 2437 | Carolyn Donovan | 3 | 3 | 1 | 0 | 0.14 |
| 2438 | Herr Serge Tröst | 2 | 2 | 12 | 6 | 0.14 |
| 2439 | Jeremi Kazberuk | 2 | 2 | 12 | 6 | 0.14 |
| 2440 | Chao Tang | 2 | 2 | 23 | 3 | 0.14 |
| 2441 | Jie Duan | 2 | 2 | 23 | 3 | 0.14 |
| 2442 | Min Bai | 2 | 2 | 23 | 3 | 0.14 |
| 2443 | Samuel Olsen | 2 | 2 | 23 | 3 | 0.14 |
| 2444 | The Wayfarers | 2 | 2 | 23 | 3 | 0.14 |
| 2445 | Xiuying Shen | 2 | 2 | 23 | 3 | 0.14 |
| 2446 | LyriCrest | 1 | 1 | 45 | 6 | 0.14 |
| 2447 | Melissa Miller | 2 | 2 | 19 | 4 | 0.14 |
| 2448 | Tao Duan | 2 | 2 | 19 | 4 | 0.14 |
| 2449 | Cosmic Reverberation | 5 | 1 | 2 | 0 | 0.14 |
| 2450 | Guiying Meng | 2 | 2 | 26 | 2 | 0.14 |
| 2451 | Timothy Schmidt | 2 | 2 | 26 | 2 | 0.14 |
| 2452 | Leif Bolzmann | 2 | 2 | 11 | 6 | 0.14 |
| 2453 | Lisa Thornton | 2 | 2 | 11 | 6 | 0.14 |
| 2454 | Alexandra Sauer-Ditschlerin | 2 | 2 | 22 | 3 | 0.14 |
| 2455 | Andrew Savage | 2 | 2 | 22 | 3 | 0.14 |
| 2456 | Heinz-Joachim Anders | 2 | 2 | 22 | 3 | 0.14 |
| 2457 | Rita Hänel | 2 | 2 | 22 | 3 | 0.14 |
| 2458 | Rosalia Bloch | 2 | 2 | 22 | 3 | 0.14 |
| 2459 | Ryan Kala | 2 | 2 | 22 | 3 | 0.14 |
| 2460 | Sandra Peterson | 2 | 2 | 22 | 3 | 0.14 |
| 2461 | Sharon Delgado | 2 | 2 | 22 | 3 | 0.14 |
| 2462 | Yan Zhong | 2 | 2 | 22 | 3 | 0.14 |
| 2463 | Chad Livingston | 1 | 1 | 44 | 6 | 0.14 |
| 2464 | Deanna Haney | 1 | 1 | 44 | 6 | 0.14 |
| 2465 | Anthony Davis | 2 | 2 | 29 | 1 | 0.14 |
| 2466 | Amalia Tartaglia | 3 | 2 | 9 | 2 | 0.14 |
| 2467 | Guiying Han | 2 | 2 | 25 | 2 | 0.14 |
| 2468 | Kendra Miller | 2 | 2 | 25 | 2 | 0.14 |
| 2469 | Yan Wan | 2 | 2 | 25 | 2 | 0.14 |
| 2470 | Genevieve Bell | 4 | 2 | 0 | 0 | 0.14 |
| 2471 | Solace Vesper | 4 | 2 | 0 | 0 | 0.14 |
| 2472 | Wei Xu | 2 | 2 | 21 | 3 | 0.14 |
| 2473 | Xia Shao | 2 | 2 | 21 | 3 | 0.14 |
| 2474 | Andrew Montgomery | 3 | 2 | 12 | 1 | 0.14 |
| 2475 | Chao Duan | 3 | 2 | 12 | 1 | 0.14 |
| 2476 | Ashley Patton | 2 | 2 | 17 | 4 | 0.14 |
| 2477 | Jessica Holmes | 2 | 2 | 17 | 4 | 0.14 |
| 2478 | Kylie Clarke | 2 | 2 | 17 | 4 | 0.14 |
| 2479 | Natasha Mcdaniel | 2 | 2 | 17 | 4 | 0.14 |
| 2480 | Xia Duan | 2 | 2 | 17 | 4 | 0.14 |
| 2481 | Xiulan Xu | 2 | 2 | 17 | 4 | 0.14 |
| 2482 | Victoria Williams | 2 | 1 | 34 | 4 | 0.14 |
| 2483 | Andrew Snyder | 3 | 2 | 8 | 2 | 0.14 |
| 2484 | Frédéric de la Coulon | 3 | 2 | 8 | 2 | 0.14 |
| 2485 | Valérie Mathieu | 3 | 2 | 8 | 2 | 0.14 |
| 2486 | Jasper Quinn | 5 | 1 | 0 | 0 | 0.14 |
| 2487 | Joe Perry | 2 | 2 | 24 | 2 | 0.14 |
| 2488 | Ming Pan | 2 | 2 | 24 | 2 | 0.14 |
| 2489 | Shannon Davis | 2 | 2 | 24 | 2 | 0.14 |
| 2490 | Xia Zhong | 2 | 2 | 24 | 2 | 0.14 |
| 2491 | Ashley Hanson | 1 | 1 | 35 | 8 | 0.14 |
| 2492 | Candice Torres | 2 | 2 | 20 | 3 | 0.14 |
| 2493 | Jun Mo | 2 | 2 | 20 | 3 | 0.14 |
| 2494 | Kimberly Smith | 2 | 2 | 20 | 3 | 0.14 |
| 2495 | Maurits van Bunschoten | 2 | 2 | 20 | 3 | 0.14 |
| 2496 | Paulo Oestrovsky | 2 | 2 | 20 | 3 | 0.14 |
| 2497 | Ping Shi | 2 | 2 | 20 | 3 | 0.14 |
| 2498 | Qiang Li | 2 | 2 | 20 | 3 | 0.14 |
| 2499 | Yong Gu | 2 | 2 | 20 | 3 | 0.14 |
| 2500 | Ping Kong | 1 | 1 | 31 | 9 | 0.14 |
| 2501 | Chao Xiang | 2 | 2 | 16 | 4 | 0.14 |
| 2502 | Gang Fu | 2 | 2 | 16 | 4 | 0.14 |
| 2503 | Mannat Johal | 2 | 2 | 16 | 4 | 0.14 |
| 2504 | Simone Säuberlich | 2 | 2 | 16 | 4 | 0.14 |
| 2505 | Yang Zhu | 2 | 2 | 27 | 1 | 0.14 |
| 2506 | Danny Williams | 1 | 1 | 27 | 10 | 0.14 |
| 2507 | Jennifer Hunt | 1 | 1 | 27 | 10 | 0.14 |
| 2508 | Katherine Sullivan | 1 | 1 | 27 | 10 | 0.14 |
| 2509 | Nicole Flynn | 1 | 1 | 27 | 10 | 0.14 |
| 2510 | Rachel Jones | 1 | 1 | 27 | 10 | 0.14 |
| 2511 | Amanda Nelson | 2 | 2 | 12 | 5 | 0.14 |
| 2512 | Chantal Stadelmann | 2 | 2 | 12 | 5 | 0.14 |
| 2513 | Dörthe Dehmel | 2 | 2 | 12 | 5 | 0.14 |
| 2514 | Larry Fields | 2 | 2 | 12 | 5 | 0.14 |
| 2515 | Stephanie Morales | 2 | 2 | 12 | 5 | 0.14 |
| 2516 | Thierry Labbé | 2 | 2 | 12 | 5 | 0.14 |
| 2517 | Kimberly Brown | 2 | 2 | 23 | 2 | 0.13 |
| 2518 | Li Hou | 2 | 2 | 23 | 2 | 0.13 |
| 2519 | Min Qiao | 2 | 2 | 23 | 2 | 0.13 |
| 2520 | Nicole Godard | 2 | 2 | 23 | 2 | 0.13 |
| 2521 | Yakshit Toor | 2 | 2 | 8 | 6 | 0.13 |
| 2522 | Alphons Donati-Pederiva | 2 | 2 | 19 | 3 | 0.13 |
| 2523 | Anthony Frost | 2 | 2 | 19 | 3 | 0.13 |
| 2524 | Augusto Villaverde Armengol | 2 | 2 | 19 | 3 | 0.13 |
| 2525 | David Jenkins | 2 | 2 | 19 | 3 | 0.13 |
| 2526 | Feliciano Pizarro Moll | 2 | 2 | 19 | 3 | 0.13 |
| 2527 | Franco Angeli | 2 | 2 | 19 | 3 | 0.13 |
| 2528 | Joshua Chase | 2 | 2 | 19 | 3 | 0.13 |
| 2529 | Jun Shi | 2 | 2 | 19 | 3 | 0.13 |
| 2530 | Maria Shea | 2 | 2 | 19 | 3 | 0.13 |
| 2531 | Stacey Campbell | 2 | 2 | 19 | 3 | 0.13 |
| 2532 | Todd Maldonado | 2 | 2 | 19 | 3 | 0.13 |
| 2533 | Jun Yang | 3 | 2 | 10 | 1 | 0.13 |
| 2534 | Tao Zhou | 2 | 2 | 15 | 4 | 0.13 |
| 2535 | John Wilkinson | 3 | 2 | 6 | 2 | 0.13 |
| 2536 | Whispered Alibi | 3 | 2 | 6 | 2 | 0.13 |
| 2537 | Chao Cai | 2 | 2 | 22 | 2 | 0.13 |
| 2538 | Cody Turner | 2 | 2 | 22 | 2 | 0.13 |
| 2539 | Stacy Watts | 2 | 2 | 22 | 2 | 0.13 |
| 2540 | Julita Koziarz | 1 | 1 | 33 | 8 | 0.13 |
| 2541 | Sylvie Scholz | 2 | 2 | 7 | 6 | 0.13 |
| 2542 | Aaron Ross | 2 | 2 | 18 | 3 | 0.13 |
| 2543 | Birthe Täsche | 2 | 2 | 18 | 3 | 0.13 |
| 2544 | Charlene Randolph | 2 | 2 | 18 | 3 | 0.13 |
| 2545 | Citrus Spirit | 2 | 2 | 18 | 3 | 0.13 |
| 2546 | Dolores Pardo Bárcena | 2 | 2 | 18 | 3 | 0.13 |
| 2547 | Fredy Lange | 2 | 2 | 18 | 3 | 0.13 |
| 2548 | Herr Oliver Schacht | 2 | 2 | 18 | 3 | 0.13 |
| 2549 | Joris Lieshout | 2 | 2 | 18 | 3 | 0.13 |
| 2550 | Michael Norman | 2 | 2 | 18 | 3 | 0.13 |
| 2551 | Pamela Roberts | 2 | 2 | 18 | 3 | 0.13 |
| 2552 | Pierluigi Telesio | 2 | 2 | 18 | 3 | 0.13 |
| 2553 | Richard Page | 2 | 2 | 18 | 3 | 0.13 |
| 2554 | Rubén Medina-Casas | 2 | 2 | 18 | 3 | 0.13 |
| 2555 | Salomón Miró Olivé | 2 | 2 | 18 | 3 | 0.13 |
| 2556 | Sigfrido Manu Morcillo Camino | 2 | 2 | 18 | 3 | 0.13 |
| 2557 | Torquato Fantini | 2 | 2 | 18 | 3 | 0.13 |
| 2558 | Vittorio Tamburello | 2 | 2 | 18 | 3 | 0.13 |
| 2559 | Paul Sanders | 2 | 2 | 14 | 4 | 0.13 |
| 2560 | Thomas Brown | 2 | 2 | 25 | 1 | 0.13 |
| 2561 | Gang Cheng | 1 | 1 | 36 | 7 | 0.13 |
| 2562 | Ewa Zwara | 2 | 2 | 10 | 5 | 0.13 |
| 2563 | Gang Zhu | 2 | 2 | 21 | 2 | 0.13 |
| 2564 | Matthew Brown | 2 | 2 | 21 | 2 | 0.13 |
| 2565 | Min Yuan | 2 | 2 | 21 | 2 | 0.13 |
| 2566 | Ming Yu | 2 | 2 | 21 | 2 | 0.13 |
| 2567 | Timothy Elliott | 2 | 2 | 21 | 2 | 0.13 |
| 2568 | Yan Bai | 2 | 2 | 21 | 2 | 0.13 |
| 2569 | Hans-Eberhard Schleich | 2 | 1 | 27 | 5 | 0.13 |
| 2570 | Tino Ring | 1 | 1 | 32 | 8 | 0.13 |
| 2571 | Daniel Mitchell | 3 | 2 | 12 | 0 | 0.13 |
| 2572 | Yan Cheng | 3 | 2 | 12 | 0 | 0.13 |
| 2573 | Crystal Sanders | 2 | 2 | 17 | 3 | 0.13 |
| 2574 | Ricardo Collins | 2 | 2 | 17 | 3 | 0.13 |
| 2575 | Tao Qian | 2 | 2 | 17 | 3 | 0.13 |
| 2576 | Anne Cobb | 1 | 1 | 39 | 6 | 0.13 |
| 2577 | Brandon Simmons | 1 | 1 | 39 | 6 | 0.13 |
| 2578 | Danielle Wright | 1 | 1 | 39 | 6 | 0.13 |
| 2579 | Lindsey Walker | 1 | 1 | 39 | 6 | 0.13 |
| 2580 | Tammy Norris | 1 | 1 | 39 | 6 | 0.13 |
| 2581 | Xiulan Song | 2 | 2 | 24 | 1 | 0.13 |
| 2582 | Eric Holland | 1 | 1 | 35 | 7 | 0.13 |
| 2583 | John Reed | 1 | 1 | 35 | 7 | 0.13 |
| 2584 | Kyle Smith | 1 | 1 | 35 | 7 | 0.13 |
| 2585 | Randy Gonzalez | 1 | 1 | 35 | 7 | 0.13 |
| 2586 | Ryan Woodard | 1 | 1 | 35 | 7 | 0.13 |
| 2587 | Caroline King | 2 | 2 | 9 | 5 | 0.13 |
| 2588 | Lindsay Nichols | 2 | 2 | 9 | 5 | 0.13 |
| 2589 | Moonlit Avenue | 2 | 2 | 9 | 5 | 0.13 |
| 2590 | Arsenio Saraceno-Mercati | 2 | 2 | 20 | 2 | 0.13 |
| 2591 | Chao Zhou | 2 | 2 | 20 | 2 | 0.13 |
| 2592 | Esther Schinke | 2 | 2 | 20 | 2 | 0.13 |
| 2593 | Fang Yao | 2 | 2 | 20 | 2 | 0.13 |
| 2594 | Gregor Dippel | 2 | 2 | 20 | 2 | 0.13 |
| 2595 | Yang Zhou | 3 | 2 | 11 | 0 | 0.13 |
| 2596 | Elżbieta Bociek | 2 | 2 | 5 | 6 | 0.13 |
| 2597 | Leah Burns | 2 | 2 | 16 | 3 | 0.13 |
| 2598 | Jordan Mullins | 2 | 1 | 22 | 6 | 0.13 |
| 2599 | Timothy Shea | 2 | 1 | 22 | 6 | 0.13 |
| 2600 | Christopher Martinez | 1 | 1 | 27 | 9 | 0.13 |
| 2601 | Russell Blake | 1 | 1 | 27 | 9 | 0.13 |
| 2602 | Katherine Francis | 1 | 1 | 38 | 6 | 0.13 |
| 2603 | Ingeborg Ullrich | 2 | 2 | 12 | 4 | 0.13 |
| 2604 | Jacob Brown | 2 | 2 | 12 | 4 | 0.13 |
| 2605 | Jonathan Wyatt | 2 | 2 | 12 | 4 | 0.13 |
| 2606 | Justin Doyle | 2 | 2 | 12 | 4 | 0.13 |
| 2607 | Sonia Suda | 2 | 2 | 12 | 4 | 0.13 |
| 2608 | Kari Williams | 1 | 1 | 34 | 7 | 0.13 |
| 2609 | Richard Morton | 1 | 1 | 34 | 7 | 0.13 |
| 2610 | Jessica Stewart | 3 | 2 | 3 | 2 | 0.13 |
| 2611 | Cheryl Waters | 2 | 2 | 19 | 2 | 0.13 |
| 2612 | Heather Moss | 2 | 2 | 19 | 2 | 0.13 |
| 2613 | Paul Bailey | 2 | 2 | 19 | 2 | 0.13 |
| 2614 | Qiang Wei | 2 | 2 | 19 | 2 | 0.13 |
| 2615 | Yong Du | 2 | 2 | 19 | 2 | 0.13 |
| 2616 | Amanda Smith | 1 | 1 | 30 | 8 | 0.13 |
| 2617 | Jonathan Hayes | 1 | 1 | 30 | 8 | 0.13 |
| 2618 | Terri Cortez | 1 | 1 | 30 | 8 | 0.13 |
| 2619 | Bibi Vos | 1 | 1 | 41 | 5 | 0.13 |
| 2620 | Cato van Holland | 1 | 1 | 41 | 5 | 0.13 |
| 2621 | Femke Mulder | 1 | 1 | 41 | 5 | 0.13 |
| 2622 | Femke van Dagsburg | 1 | 1 | 41 | 5 | 0.13 |
| 2623 | Jesper Heijmans | 1 | 1 | 41 | 5 | 0.13 |
| 2624 | Julie Schatteleijn-Haack | 1 | 1 | 41 | 5 | 0.13 |
| 2625 | Julie van der Noot | 1 | 1 | 41 | 5 | 0.13 |
| 2626 | Mark Hellevoort-Verbruggen | 1 | 1 | 41 | 5 | 0.13 |
| 2627 | Mats Bökenkamp | 1 | 1 | 41 | 5 | 0.13 |
| 2628 | Piotr Smoter | 1 | 1 | 41 | 5 | 0.13 |
| 2629 | Sofie van der Hoeven | 1 | 1 | 41 | 5 | 0.13 |
| 2630 | Szymon Samol | 1 | 1 | 41 | 5 | 0.13 |
| 2631 | Courtney Carroll | 2 | 2 | 15 | 3 | 0.13 |
| 2632 | Hans Georg Eigenwillig-Reising | 2 | 2 | 15 | 3 | 0.13 |
| 2633 | Kelly Munoz | 2 | 2 | 15 | 3 | 0.13 |
| 2634 | Min Hao | 2 | 2 | 15 | 3 | 0.13 |
| 2635 | Edward Morgan | 2 | 1 | 21 | 6 | 0.13 |
| 2636 | Alejandra Gould | 1 | 1 | 15 | 12 | 0.13 |
| 2637 | John Dean | 1 | 1 | 15 | 12 | 0.13 |
| 2638 | Jie Qiao | 2 | 2 | 26 | 0 | 0.13 |
| 2639 | Sherry Russell | 2 | 2 | 11 | 4 | 0.13 |
| 2640 | Tammy Mcdonald | 2 | 2 | 11 | 4 | 0.13 |
| 2641 | Guiying Fang | 2 | 2 | 22 | 1 | 0.13 |
| 2642 | Diya Swamy | 3 | 2 | 2 | 2 | 0.13 |
| 2643 | Christina Mendoza | 2 | 2 | 7 | 5 | 0.13 |
| 2644 | Candela Pallarès Artigas | 2 | 2 | 18 | 2 | 0.13 |
| 2645 | Fang Lei | 2 | 2 | 18 | 2 | 0.13 |
| 2646 | Gang Han | 2 | 2 | 18 | 2 | 0.13 |
| 2647 | Li Lai | 2 | 2 | 18 | 2 | 0.13 |
| 2648 | Miss Amy Harmon | 2 | 2 | 18 | 2 | 0.13 |
| 2649 | Qiang Zhu | 2 | 2 | 18 | 2 | 0.13 |
| 2650 | Ricarda Nélida Palmer Serra | 2 | 2 | 18 | 2 | 0.13 |
| 2651 | Yan Ding | 2 | 2 | 18 | 2 | 0.13 |
| 2652 | Aniela Mijas | 1 | 1 | 18 | 11 | 0.13 |
| 2653 | Agnès de Leroy | 1 | 1 | 29 | 8 | 0.13 |
| 2654 | Gang Jiang | 2 | 2 | 14 | 3 | 0.13 |
| 2655 | Kimberly Nelson | 2 | 2 | 14 | 3 | 0.13 |
| 2656 | Stephanie Montoya | 2 | 2 | 14 | 3 | 0.13 |
| 2657 | Apolonia Chlebda | 1 | 1 | 14 | 12 | 0.13 |
| 2658 | Mariner's Refrain | 4 | 1 | 6 | 1 | 0.13 |
| 2659 | David Franklin | 3 | 2 | 5 | 1 | 0.13 |
| 2660 | Desert Echoes | 3 | 2 | 5 | 1 | 0.13 |
| 2661 | Cameron Faulkner | 2 | 2 | 10 | 4 | 0.13 |
| 2662 | Chao Hao | 2 | 2 | 10 | 4 | 0.13 |
| 2663 | Peripheral Circuit | 2 | 2 | 10 | 4 | 0.13 |
| 2664 | Pivotal Trinity | 2 | 2 | 10 | 4 | 0.13 |
| 2665 | The Feast | 2 | 2 | 10 | 4 | 0.13 |
| 2666 | Timothy Lewis | 2 | 2 | 10 | 4 | 0.13 |
| 2667 | Jason Evans | 2 | 2 | 21 | 1 | 0.13 |
| 2668 | Courtney Phillips | 1 | 1 | 32 | 7 | 0.13 |
| 2669 | Kelli Turner | 1 | 1 | 32 | 7 | 0.13 |
| 2670 | Latasha Chavez | 1 | 1 | 32 | 7 | 0.13 |
| 2671 | Giacinto Maderna | 2 | 2 | 6 | 5 | 0.13 |
| 2672 | Janos Zimmer | 2 | 2 | 6 | 5 | 0.13 |
| 2673 | Krzysztof Linda | 2 | 2 | 6 | 5 | 0.13 |
| 2674 | Beppe Agazzi-Muratori | 2 | 2 | 17 | 2 | 0.12 |
| 2675 | Hans-Theo Eckbauer-Dehmel | 2 | 2 | 17 | 2 | 0.12 |
| 2676 | Lei Zhang | 2 | 2 | 17 | 2 | 0.12 |
| 2677 | Ming Feng | 2 | 2 | 17 | 2 | 0.12 |
| 2678 | Na Qiu | 2 | 2 | 17 | 2 | 0.12 |
| 2679 | Xia Gu | 2 | 2 | 17 | 2 | 0.12 |
| 2680 | Xia Shen | 2 | 2 | 17 | 2 | 0.12 |
| 2681 | Yang Lu | 2 | 2 | 17 | 2 | 0.12 |
| 2682 | Robert Peters | 1 | 1 | 28 | 8 | 0.12 |
| 2683 | Brenda Dunn | 2 | 2 | 13 | 3 | 0.12 |
| 2684 | Cosmic Sankey | 2 | 2 | 13 | 3 | 0.12 |
| 2685 | Cristina Williams | 2 | 2 | 13 | 3 | 0.12 |
| 2686 | Emily Glenn | 2 | 2 | 13 | 3 | 0.12 |
| 2687 | Ewa Kucz | 2 | 2 | 13 | 3 | 0.12 |
| 2688 | Jacqueline Monroe | 2 | 2 | 13 | 3 | 0.12 |
| 2689 | Jennifer Collins | 2 | 2 | 13 | 3 | 0.12 |
| 2690 | Mark Sparks | 2 | 2 | 13 | 3 | 0.12 |
| 2691 | Norma Huff | 2 | 1 | 30 | 3 | 0.12 |
| 2692 | Asuka Fukuda | 2 | 2 | 9 | 4 | 0.12 |
| 2693 | Crystal Norman | 2 | 2 | 20 | 1 | 0.12 |
| 2694 | Justin Campbell | 2 | 2 | 20 | 1 | 0.12 |
| 2695 | Mark Nichols | 2 | 2 | 20 | 1 | 0.12 |
| 2696 | Xia Qian | 2 | 2 | 20 | 1 | 0.12 |
| 2697 | Xiulan Lei | 2 | 2 | 20 | 1 | 0.12 |
| 2698 | Matthew Smith | 2 | 1 | 26 | 4 | 0.12 |
| 2699 | Hortense du Dijoux | 2 | 2 | 16 | 2 | 0.12 |
| 2700 | Jun Kong | 2 | 2 | 16 | 2 | 0.12 |
| 2701 | Kunigunde Pechel | 2 | 2 | 16 | 2 | 0.12 |
| 2702 | Li Kang | 2 | 2 | 16 | 2 | 0.12 |
| 2703 | Li Liu | 2 | 2 | 16 | 2 | 0.12 |
| 2704 | Melinda Gregory | 2 | 2 | 16 | 2 | 0.12 |
| 2705 | Na Shi | 2 | 2 | 16 | 2 | 0.12 |
| 2706 | Nicholas Chen | 2 | 2 | 16 | 2 | 0.12 |
| 2707 | Stacey Christensen | 2 | 2 | 16 | 2 | 0.12 |
| 2708 | Vincent Seifert | 2 | 2 | 16 | 2 | 0.12 |
| 2709 | Wei Xue | 2 | 2 | 16 | 2 | 0.12 |
| 2710 | Xia Su | 2 | 2 | 16 | 2 | 0.12 |
| 2711 | Yang Meng | 2 | 2 | 16 | 2 | 0.12 |
| 2712 | Erica Hernandez | 1 | 1 | 27 | 8 | 0.12 |
| 2713 | Jules Paris | 1 | 1 | 27 | 8 | 0.12 |
| 2714 | Kathy Johnson | 1 | 1 | 27 | 8 | 0.12 |
| 2715 | Lee Butler | 1 | 1 | 27 | 8 | 0.12 |
| 2716 | Livia Blewanus | 1 | 1 | 27 | 8 | 0.12 |
| 2717 | Antonio Johnson | 2 | 2 | 12 | 3 | 0.12 |
| 2718 | Brooke Olson | 2 | 2 | 12 | 3 | 0.12 |
| 2719 | Dina Borroni | 2 | 2 | 12 | 3 | 0.12 |
| 2720 | Jing Jia | 2 | 2 | 12 | 3 | 0.12 |
| 2721 | Joseph Figueroa | 2 | 2 | 12 | 3 | 0.12 |
| 2722 | Matilda Zarlino | 2 | 2 | 12 | 3 | 0.12 |
| 2723 | Pierangelo Papafava | 2 | 2 | 12 | 3 | 0.12 |
| 2724 | Silver Seraph | 2 | 2 | 12 | 3 | 0.12 |
| 2725 | Victoria Higgins | 2 | 2 | 12 | 3 | 0.12 |
| 2726 | Heather Wood | 1 | 1 | 34 | 6 | 0.12 |
| 2727 | Laura Jefferson | 1 | 1 | 34 | 6 | 0.12 |
| 2728 | Hansh Ramanathan | 3 | 2 | 3 | 1 | 0.12 |
| 2729 | Gregory Reeves | 2 | 2 | 19 | 1 | 0.12 |
| 2730 | Leo Schuster | 2 | 2 | 19 | 1 | 0.12 |
| 2731 | Qiang Jiang | 2 | 2 | 19 | 1 | 0.12 |
| 2732 | Yang Su | 2 | 2 | 19 | 1 | 0.12 |
| 2733 | Eric Reyes | 1 | 1 | 30 | 7 | 0.12 |
| 2734 | Monica Franco | 1 | 1 | 30 | 7 | 0.12 |
| 2735 | Sharon Gallegos | 1 | 1 | 30 | 7 | 0.12 |
| 2736 | Gang Chang | 2 | 2 | 15 | 2 | 0.12 |
| 2737 | Min Zhong | 2 | 2 | 15 | 2 | 0.12 |
| 2738 | Morgan Hernandez | 2 | 2 | 15 | 2 | 0.12 |
| 2739 | Patricia Pope | 2 | 2 | 15 | 2 | 0.12 |
| 2740 | Ping Liang | 2 | 2 | 15 | 2 | 0.12 |
| 2741 | Tao Xiang | 2 | 2 | 15 | 2 | 0.12 |
| 2742 | Xiuying Mao | 2 | 2 | 15 | 2 | 0.12 |
| 2743 | Yang Cai | 2 | 2 | 15 | 2 | 0.12 |
| 2744 | Yang Yin | 2 | 2 | 15 | 2 | 0.12 |
| 2745 | Yong Chang | 2 | 2 | 15 | 2 | 0.12 |
| 2746 | Michael Warner | 1 | 1 | 26 | 8 | 0.12 |
| 2747 | Onkar Chacko | 1 | 1 | 26 | 8 | 0.12 |
| 2748 | Robert Long | 1 | 1 | 26 | 8 | 0.12 |
| 2749 | Aaron Logan | 1 | 1 | 37 | 5 | 0.12 |
| 2750 | Carol Hanna | 1 | 1 | 37 | 5 | 0.12 |
| 2751 | Kevin Kidd | 1 | 1 | 37 | 5 | 0.12 |
| 2752 | Megan Dunn | 1 | 1 | 37 | 5 | 0.12 |
| 2753 | William Moore | 1 | 1 | 37 | 5 | 0.12 |
| 2754 | Andrew Lang | 2 | 2 | 11 | 3 | 0.12 |
| 2755 | Hanne-Lore Scholl-Heser | 2 | 2 | 11 | 3 | 0.12 |
| 2756 | Hildegund Wilmsen | 2 | 2 | 11 | 3 | 0.12 |
| 2757 | Jutta Matthäi | 2 | 2 | 11 | 3 | 0.12 |
| 2758 | Laetitia Petitjean | 2 | 2 | 11 | 3 | 0.12 |
| 2759 | Madeleine Pineau | 2 | 2 | 11 | 3 | 0.12 |
| 2760 | Qiang Wang | 2 | 2 | 11 | 3 | 0.12 |
| 2761 | Rosalie Hettner-Warmer | 2 | 2 | 11 | 3 | 0.12 |
| 2762 | Susan Da Silva | 2 | 2 | 11 | 3 | 0.12 |
| 2763 | Xia Xiang | 2 | 2 | 11 | 3 | 0.12 |
| 2764 | Yesenia Tyler | 2 | 2 | 11 | 3 | 0.12 |
| 2765 | Émilie Maillet | 2 | 2 | 11 | 3 | 0.12 |
| 2766 | Carl Osborne | 2 | 2 | 22 | 0 | 0.12 |
| 2767 | Maurice Mathieu | 2 | 1 | 28 | 3 | 0.12 |
| 2768 | Emily Jackson | 1 | 1 | 33 | 6 | 0.12 |
| 2769 | Na Wan | 1 | 0 | 39 | 9 | 0.12 |
| 2770 | Beverly Thompson | 2 | 2 | 7 | 4 | 0.12 |
| 2771 | Jennifer Hart | 2 | 2 | 18 | 1 | 0.12 |
| 2772 | Min Ma | 2 | 2 | 18 | 1 | 0.12 |
| 2773 | Benjamin Mercer | 2 | 2 | 14 | 2 | 0.12 |
| 2774 | Chao Cao | 2 | 2 | 14 | 2 | 0.12 |
| 2775 | Hansjürgen Pechel | 2 | 2 | 14 | 2 | 0.12 |
| 2776 | Jie Xia | 2 | 2 | 14 | 2 | 0.12 |
| 2777 | Lei Liu | 2 | 2 | 14 | 2 | 0.12 |
| 2778 | Lilian Gieß | 2 | 2 | 14 | 2 | 0.12 |
| 2779 | Mario Stumpf | 2 | 2 | 14 | 2 | 0.12 |
| 2780 | Marvin Holzapfel | 2 | 2 | 14 | 2 | 0.12 |
| 2781 | Ming Tang | 2 | 2 | 14 | 2 | 0.12 |
| 2782 | Qiang Zou | 2 | 2 | 14 | 2 | 0.12 |
| 2783 | Tao Ma | 2 | 2 | 14 | 2 | 0.12 |
| 2784 | John Bradley | 1 | 1 | 25 | 8 | 0.12 |
| 2785 | Kristina Allen | 1 | 1 | 25 | 8 | 0.12 |
| 2786 | Stephanie Fritz | 1 | 1 | 25 | 8 | 0.12 |
| 2787 | Emilie Rudolph | 2 | 2 | 10 | 3 | 0.12 |
| 2788 | Guiying Xiang | 2 | 2 | 10 | 3 | 0.12 |
| 2789 | Marlene Rose | 2 | 2 | 10 | 3 | 0.12 |
| 2790 | Robert Nunez | 2 | 2 | 10 | 3 | 0.12 |
| 2791 | Tammy Fields | 2 | 2 | 10 | 3 | 0.12 |
| 2792 | Warm Circuit | 2 | 2 | 10 | 3 | 0.12 |
| 2793 | Jing He | 2 | 2 | 21 | 0 | 0.12 |
| 2794 | Marcel Camus-Meunier | 2 | 2 | 6 | 4 | 0.12 |
| 2795 | Chao Luo | 2 | 2 | 17 | 1 | 0.12 |
| 2796 | Jie Sun | 2 | 2 | 17 | 1 | 0.12 |
| 2797 | Li Yuan | 2 | 2 | 17 | 1 | 0.12 |
| 2798 | Yang Qiu | 2 | 2 | 17 | 1 | 0.12 |
| 2799 | Andrzej Schottin-Mühle | 2 | 2 | 13 | 2 | 0.12 |
| 2800 | Chao Xue | 2 | 2 | 13 | 2 | 0.12 |
| 2801 | Daria Boucsein | 2 | 2 | 13 | 2 | 0.12 |
| 2802 | David Williams | 2 | 2 | 13 | 2 | 0.12 |
| 2803 | Gang Li | 2 | 2 | 13 | 2 | 0.12 |
| 2804 | Jean Buisson | 2 | 2 | 13 | 2 | 0.12 |
| 2805 | Kayla Campbell | 2 | 2 | 13 | 2 | 0.12 |
| 2806 | Lei Yu | 2 | 2 | 13 | 2 | 0.12 |
| 2807 | Min Cheng | 2 | 2 | 13 | 2 | 0.12 |
| 2808 | Na Yu | 2 | 2 | 13 | 2 | 0.12 |
| 2809 | Orhan Krein | 2 | 2 | 13 | 2 | 0.12 |
| 2810 | Shawn Wilson | 2 | 2 | 13 | 2 | 0.12 |
| 2811 | Sophia Baracca-Solimena | 2 | 2 | 13 | 2 | 0.12 |
| 2812 | Vincentio Galiazzo | 2 | 2 | 13 | 2 | 0.12 |
| 2813 | Eliza Brooks | 3 | 2 | 4 | 0 | 0.12 |
| 2814 | Imelda Zaguri | 3 | 2 | 4 | 0 | 0.12 |
| 2815 | Jasper Reed | 3 | 2 | 4 | 0 | 0.12 |
| 2816 | Nanni Telesio | 3 | 2 | 4 | 0 | 0.12 |
| 2817 | Arkadiusz Flisiak | 2 | 2 | 9 | 3 | 0.12 |
| 2818 | Dusan Ullmann | 2 | 2 | 9 | 3 | 0.12 |
| 2819 | Indranil Vala | 2 | 2 | 9 | 3 | 0.12 |
| 2820 | Kashvi Keer | 2 | 2 | 9 | 3 | 0.12 |
| 2821 | Lenn Blaak | 2 | 2 | 9 | 3 | 0.12 |
| 2822 | Los Leones del Valle | 2 | 2 | 20 | 0 | 0.12 |
| 2823 | Xia Yin | 2 | 2 | 20 | 0 | 0.12 |
| 2824 | Lisa Steele | 1 | 1 | 31 | 6 | 0.12 |
| 2825 | Elizabeth Shepherd | 2 | 2 | 5 | 4 | 0.12 |
| 2826 | Alma Davids | 2 | 2 | 16 | 1 | 0.12 |
| 2827 | Christopher Hill | 2 | 2 | 16 | 1 | 0.12 |
| 2828 | Guiying Liang | 2 | 2 | 16 | 1 | 0.12 |
| 2829 | Guiying Ye | 2 | 2 | 16 | 1 | 0.12 |
| 2830 | Nicole Simmons | 2 | 2 | 16 | 1 | 0.12 |
| 2831 | Tao Lai | 2 | 2 | 16 | 1 | 0.12 |
| 2832 | Yang Lin | 2 | 2 | 16 | 1 | 0.12 |
| 2833 | Amanda Tucker | 2 | 2 | 12 | 2 | 0.12 |
| 2834 | Anthony Hancock | 2 | 2 | 12 | 2 | 0.12 |
| 2835 | Cipriano Peranda | 2 | 2 | 12 | 2 | 0.12 |
| 2836 | Colleen Frank PhD | 2 | 2 | 12 | 2 | 0.12 |
| 2837 | Deanna Hines | 2 | 2 | 12 | 2 | 0.12 |
| 2838 | Henri Drubin | 2 | 2 | 12 | 2 | 0.12 |
| 2839 | Kristin Floyd | 2 | 2 | 12 | 2 | 0.12 |
| 2840 | Kristina Romero | 2 | 2 | 12 | 2 | 0.12 |
| 2841 | Min Zeng | 2 | 2 | 12 | 2 | 0.12 |
| 2842 | Nicholas Garcia | 2 | 2 | 12 | 2 | 0.12 |
| 2843 | Xia Meng | 2 | 2 | 12 | 2 | 0.12 |
| 2844 | Yan Shao | 2 | 2 | 12 | 2 | 0.12 |
| 2845 | Nadia van Dooren-de Jode Vastraedsd | 2 | 1 | 29 | 2 | 0.12 |
| 2846 | Christopher Hernandez | 1 | 1 | 23 | 8 | 0.12 |
| 2847 | Deborah Hernandez | 1 | 1 | 34 | 5 | 0.12 |
| 2848 | Gregory Thompson | 1 | 1 | 34 | 5 | 0.12 |
| 2849 | Hiroshi Shimizu | 1 | 1 | 34 | 5 | 0.12 |
| 2850 | Adam Nelson | 2 | 2 | 8 | 3 | 0.12 |
| 2851 | Anthony Cox | 2 | 2 | 8 | 3 | 0.12 |
| 2852 | Anto Hornich | 2 | 2 | 8 | 3 | 0.12 |
| 2853 | David Silva | 2 | 2 | 8 | 3 | 0.12 |
| 2854 | Elizabeth Nguyen | 2 | 2 | 8 | 3 | 0.12 |
| 2855 | Imelda Staude-Trupp | 2 | 2 | 8 | 3 | 0.12 |
| 2856 | James Green | 2 | 2 | 8 | 3 | 0.12 |
| 2857 | Kelly Brown | 2 | 2 | 8 | 3 | 0.12 |
| 2858 | Michael Hartman | 2 | 2 | 8 | 3 | 0.12 |
| 2859 | Steven Fox | 2 | 2 | 8 | 3 | 0.12 |
| 2860 | Tadeusz Langern | 2 | 2 | 8 | 3 | 0.12 |
| 2861 | Yang Li | 2 | 2 | 19 | 0 | 0.12 |
| 2862 | James Clark | 1 | 1 | 30 | 6 | 0.12 |
| 2863 | Chao Liang | 2 | 2 | 15 | 1 | 0.12 |
| 2864 | Evamaria Geisel | 2 | 2 | 15 | 1 | 0.12 |
| 2865 | Gang Liao | 2 | 2 | 15 | 1 | 0.12 |
| 2866 | Gang Qiao | 2 | 2 | 15 | 1 | 0.12 |
| 2867 | Guiying Kong | 2 | 2 | 15 | 1 | 0.12 |
| 2868 | Jing Cao | 2 | 2 | 15 | 1 | 0.12 |
| 2869 | Jing Ma | 2 | 2 | 15 | 1 | 0.12 |
| 2870 | Karen Williams | 2 | 2 | 15 | 1 | 0.12 |
| 2871 | Lei Guo | 2 | 2 | 15 | 1 | 0.12 |
| 2872 | Ping Ma | 2 | 2 | 15 | 1 | 0.12 |
| 2873 | Ping Xue | 2 | 2 | 15 | 1 | 0.12 |
| 2874 | Sonic Disintegration Protocol | 2 | 2 | 15 | 1 | 0.12 |
| 2875 | Xia Wen | 2 | 2 | 15 | 1 | 0.12 |
| 2876 | Yan Cao | 2 | 2 | 15 | 1 | 0.12 |
| 2877 | Georgina Piñol-Guerra | 1 | 0 | 43 | 7 | 0.12 |
| 2878 | Lalo Salgado Cazorla | 1 | 0 | 43 | 7 | 0.12 |
| 2879 | Luigina Stoppani-Sandi | 1 | 0 | 43 | 7 | 0.12 |
| 2880 | Arhaan Batta | 2 | 2 | 11 | 2 | 0.11 |
| 2881 | Billy Tyler | 2 | 2 | 11 | 2 | 0.11 |
| 2882 | Chao Mao | 2 | 2 | 11 | 2 | 0.11 |
| 2883 | Electric Twist | 2 | 2 | 11 | 2 | 0.11 |
| 2884 | Ida Ryfa | 2 | 2 | 11 | 2 | 0.11 |
| 2885 | Ivory Pulse | 2 | 2 | 11 | 2 | 0.11 |
| 2886 | Klara Parkitna | 2 | 2 | 11 | 2 | 0.11 |
| 2887 | Michael Jones | 2 | 2 | 11 | 2 | 0.11 |
| 2888 | Na Tang | 2 | 2 | 11 | 2 | 0.11 |
| 2889 | Nicholas Riddle | 2 | 2 | 11 | 2 | 0.11 |
| 2890 | Sarah Fernandez | 2 | 2 | 11 | 2 | 0.11 |
| 2891 | The Midnight Sentinels | 2 | 2 | 11 | 2 | 0.11 |
| 2892 | The Lunar Tides | 4 | 1 | 3 | 0 | 0.11 |
| 2893 | Jared Mercer | 1 | 1 | 33 | 5 | 0.11 |
| 2894 | Kim Knight | 1 | 1 | 33 | 5 | 0.11 |
| 2895 | Cilly Säuberlich | 2 | 2 | 7 | 3 | 0.11 |
| 2896 | Ian Foster | 2 | 2 | 7 | 3 | 0.11 |
| 2897 | Mehdi Hering | 2 | 2 | 7 | 3 | 0.11 |
| 2898 | Reinhild Krein | 2 | 2 | 7 | 3 | 0.11 |
| 2899 | The Chaotic Realm of Elliot Flame | 2 | 2 | 7 | 3 | 0.11 |
| 2900 | Tillmann Klemm | 2 | 2 | 7 | 3 | 0.11 |
| 2901 | Chao Hou | 2 | 2 | 14 | 1 | 0.11 |
| 2902 | Chao Shao | 2 | 2 | 14 | 1 | 0.11 |
| 2903 | Daniel Johnson | 2 | 2 | 14 | 1 | 0.11 |
| 2904 | Guiying Xu | 2 | 2 | 14 | 1 | 0.11 |
| 2905 | Kristi Bowers | 2 | 2 | 14 | 1 | 0.11 |
| 2906 | Lei Zou | 2 | 2 | 14 | 1 | 0.11 |
| 2907 | Min Zheng | 2 | 2 | 14 | 1 | 0.11 |
| 2908 | Qiang Hao | 2 | 2 | 14 | 1 | 0.11 |
| 2909 | Qiang Zheng | 2 | 2 | 14 | 1 | 0.11 |
| 2910 | Thomas Ball | 2 | 2 | 14 | 1 | 0.11 |
| 2911 | Xia Liao | 2 | 2 | 14 | 1 | 0.11 |
| 2912 | Xia Xu | 2 | 2 | 14 | 1 | 0.11 |
| 2913 | Xiuying Zou | 2 | 2 | 14 | 1 | 0.11 |
| 2914 | Yong Wu | 2 | 2 | 14 | 1 | 0.11 |
| 2915 | Zaira Balotelli-Peano | 2 | 2 | 14 | 1 | 0.11 |
| 2916 | Akemi Sato | 2 | 2 | 10 | 2 | 0.11 |
| 2917 | Duuk Schokman | 2 | 2 | 10 | 2 | 0.11 |
| 2918 | Fang Deng | 2 | 2 | 10 | 2 | 0.11 |
| 2919 | Gioele Monte | 2 | 2 | 10 | 2 | 0.11 |
| 2920 | Hiroshi Nakamura | 2 | 2 | 10 | 2 | 0.11 |
| 2921 | Juan Hao | 2 | 2 | 10 | 2 | 0.11 |
| 2922 | Jurre Kunen | 2 | 2 | 10 | 2 | 0.11 |
| 2923 | Karl-Friedrich auch Schlauchin | 2 | 2 | 10 | 2 | 0.11 |
| 2924 | Kenan Reichmann | 2 | 2 | 10 | 2 | 0.11 |
| 2925 | Lauretta Pasolini | 2 | 2 | 10 | 2 | 0.11 |
| 2926 | Linda Santos | 2 | 2 | 10 | 2 | 0.11 |
| 2927 | Lukas Waltrade Walderade-van Dam | 2 | 2 | 10 | 2 | 0.11 |
| 2928 | Marcin Maksimowicz | 2 | 2 | 10 | 2 | 0.11 |
| 2929 | Melodic Mischief | 2 | 2 | 10 | 2 | 0.11 |
| 2930 | Mila Hellevoort-Robbrechts Bruijne | 2 | 2 | 10 | 2 | 0.11 |
| 2931 | Rei Hayashi | 2 | 2 | 10 | 2 | 0.11 |
| 2932 | Sotaro Sato | 2 | 2 | 10 | 2 | 0.11 |
| 2933 | Tao Cheng | 2 | 2 | 10 | 2 | 0.11 |
| 2934 | Yasuhiro Yamamoto | 2 | 2 | 10 | 2 | 0.11 |
| 2935 | Yosuke Yamamoto | 2 | 2 | 10 | 2 | 0.11 |
| 2936 | Jerry Johnson | 2 | 2 | 6 | 3 | 0.11 |
| 2937 | Julian Biegała | 2 | 2 | 6 | 3 | 0.11 |
| 2938 | Gang Ren | 2 | 2 | 17 | 0 | 0.11 |
| 2939 | Juan Ren | 2 | 2 | 17 | 0 | 0.11 |
| 2940 | Falko Mielcarek | 1 | 1 | 17 | 9 | 0.11 |
| 2941 | Brooke Chang | 2 | 2 | 13 | 1 | 0.11 |
| 2942 | Carolyn Salas | 2 | 2 | 13 | 1 | 0.11 |
| 2943 | Guiying Deng | 2 | 2 | 13 | 1 | 0.11 |
| 2944 | Li Ding | 2 | 2 | 13 | 1 | 0.11 |
| 2945 | Min Lu | 2 | 2 | 13 | 1 | 0.11 |
| 2946 | Nancy Smith | 2 | 2 | 13 | 1 | 0.11 |
| 2947 | Qiang Liang | 2 | 2 | 13 | 1 | 0.11 |
| 2948 | Qiang Tian | 2 | 2 | 13 | 1 | 0.11 |
| 2949 | Wei Xie | 2 | 2 | 13 | 1 | 0.11 |
| 2950 | Xiulan Qiu | 2 | 2 | 13 | 1 | 0.11 |
| 2951 | Alexander Parsons | 2 | 2 | 9 | 2 | 0.11 |
| 2952 | Amanda Marquez | 2 | 2 | 9 | 2 | 0.11 |
| 2953 | Andrea Smith | 2 | 2 | 9 | 2 | 0.11 |
| 2954 | Charlene Lopez | 2 | 2 | 9 | 2 | 0.11 |
| 2955 | Frederick Freeman | 2 | 2 | 9 | 2 | 0.11 |
| 2956 | Jason Underwood | 2 | 2 | 9 | 2 | 0.11 |
| 2957 | Martin Johnson | 2 | 2 | 9 | 2 | 0.11 |
| 2958 | Michael Craig | 2 | 2 | 9 | 2 | 0.11 |
| 2959 | Ping Lin | 2 | 2 | 9 | 2 | 0.11 |
| 2960 | Daniel Mccormick | 1 | 1 | 31 | 5 | 0.11 |
| 2961 | Gabriel Gaudin | 1 | 1 | 31 | 5 | 0.11 |
| 2962 | Liberto Antonacci | 1 | 1 | 31 | 5 | 0.11 |
| 2963 | Valeria Perini | 1 | 1 | 31 | 5 | 0.11 |
| 2964 | Brittany Mcguire | 2 | 2 | 5 | 3 | 0.11 |
| 2965 | Tamara Brown | 1 | 1 | 27 | 6 | 0.11 |
| 2966 | Chao Ren | 2 | 2 | 12 | 1 | 0.11 |
| 2967 | Fang He | 2 | 2 | 12 | 1 | 0.11 |
| 2968 | Guiying Feng | 2 | 2 | 12 | 1 | 0.11 |
| 2969 | Jennifer Mccoy | 2 | 2 | 12 | 1 | 0.11 |
| 2970 | Jie Lin | 2 | 2 | 12 | 1 | 0.11 |
| 2971 | Jie Ye | 2 | 2 | 12 | 1 | 0.11 |
| 2972 | Jing Qiu | 2 | 2 | 12 | 1 | 0.11 |
| 2973 | Melissa Garcia | 2 | 2 | 12 | 1 | 0.11 |
| 2974 | Min Wei | 2 | 2 | 12 | 1 | 0.11 |
| 2975 | Ming Xie | 2 | 2 | 12 | 1 | 0.11 |
| 2976 | Ping Han | 2 | 2 | 12 | 1 | 0.11 |
| 2977 | Richard Davis | 2 | 2 | 12 | 1 | 0.11 |
| 2978 | Rosaria Ferrara | 2 | 2 | 12 | 1 | 0.11 |
| 2979 | Tao Chen | 2 | 2 | 12 | 1 | 0.11 |
| 2980 | Valentina Ungaretti-Pucci | 2 | 2 | 12 | 1 | 0.11 |
| 2981 | Xiuying Lu | 2 | 2 | 12 | 1 | 0.11 |
| 2982 | Yan Hu | 2 | 2 | 12 | 1 | 0.11 |
| 2983 | Levi Stewart | 1 | 1 | 34 | 4 | 0.11 |
| 2984 | Lori Delgado | 1 | 1 | 34 | 4 | 0.11 |
| 2985 | Whispered Resonance | 3 | 1 | 9 | 2 | 0.11 |
| 2986 | Amanda Morales | 2 | 2 | 8 | 2 | 0.11 |
| 2987 | April Brown | 2 | 2 | 8 | 2 | 0.11 |
| 2988 | Barbara Moore | 2 | 2 | 8 | 2 | 0.11 |
| 2989 | Bryan Richardson | 2 | 2 | 8 | 2 | 0.11 |
| 2990 | Charo Perez Castillo | 2 | 2 | 8 | 2 | 0.11 |
| 2991 | Daniel Collins | 2 | 2 | 8 | 2 | 0.11 |
| 2992 | Danny Craig | 2 | 2 | 8 | 2 | 0.11 |
| 2993 | Frédérique Peron | 2 | 2 | 8 | 2 | 0.11 |
| 2994 | Haruka Nishimura | 2 | 2 | 8 | 2 | 0.11 |
| 2995 | Midnight Feather | 2 | 2 | 8 | 2 | 0.11 |
| 2996 | Philippe Franke | 2 | 2 | 8 | 2 | 0.11 |
| 2997 | Shohei Ito | 2 | 2 | 8 | 2 | 0.11 |
| 2998 | The Rhythm Rascals | 2 | 2 | 8 | 2 | 0.11 |
| 2999 | Ashen Valor | 5 | 0 | 1 | 0 | 0.11 |
| 3000 | Amy Mack | 2 | 1 | 25 | 2 | 0.11 |
| 3001 | Joann Cunningham | 2 | 1 | 25 | 2 | 0.11 |
| 3002 | Mark Crawford | 1 | 1 | 19 | 8 | 0.11 |
| 3003 | Alex Thomas | 2 | 2 | 4 | 3 | 0.11 |
| 3004 | Amber Watson | 2 | 2 | 4 | 3 | 0.11 |
| 3005 | Julie Thompson | 2 | 2 | 4 | 3 | 0.11 |
| 3006 | Laura Lee | 2 | 2 | 4 | 3 | 0.11 |
| 3007 | Dolores Tasso | 2 | 2 | 15 | 0 | 0.11 |
| 3008 | Mark Trujillo | 2 | 2 | 15 | 0 | 0.11 |
| 3009 | Na Hao | 2 | 2 | 15 | 0 | 0.11 |
| 3010 | Renzo Dallapé | 2 | 2 | 15 | 0 | 0.11 |
| 3011 | Cory Wall | 2 | 2 | 11 | 1 | 0.11 |
| 3012 | Destiny Norman | 2 | 2 | 11 | 1 | 0.11 |
| 3013 | Dominique Ramos | 2 | 2 | 11 | 1 | 0.11 |
| 3014 | Gang Yi | 2 | 2 | 11 | 1 | 0.11 |
| 3015 | Jeffrey Thompson | 2 | 2 | 11 | 1 | 0.11 |
| 3016 | Jing Su | 2 | 2 | 11 | 1 | 0.11 |
| 3017 | Juan Hou | 2 | 2 | 11 | 1 | 0.11 |
| 3018 | Juan Luo | 2 | 2 | 11 | 1 | 0.11 |
| 3019 | Jun Fan | 2 | 2 | 11 | 1 | 0.11 |
| 3020 | Kevin Morrow | 2 | 2 | 11 | 1 | 0.11 |
| 3021 | Min Pan | 2 | 2 | 11 | 1 | 0.11 |
| 3022 | Na Fu | 2 | 2 | 11 | 1 | 0.11 |
| 3023 | Qiang Xiang | 2 | 2 | 11 | 1 | 0.11 |
| 3024 | Qiang Yan | 2 | 2 | 11 | 1 | 0.11 |
| 3025 | Tao Shao | 2 | 2 | 11 | 1 | 0.11 |
| 3026 | Xiuying Wan | 2 | 2 | 11 | 1 | 0.11 |
| 3027 | Yong Kong | 2 | 2 | 11 | 1 | 0.11 |
| 3028 | Annaliese Bolnbach | 2 | 2 | 7 | 2 | 0.11 |
| 3029 | Arne Baum | 2 | 2 | 7 | 2 | 0.11 |
| 3030 | Claudia Lee | 2 | 2 | 7 | 2 | 0.11 |
| 3031 | Hans-Gerhard Kuhl | 2 | 2 | 7 | 2 | 0.11 |
| 3032 | Hinrich Dörschner | 2 | 2 | 7 | 2 | 0.11 |
| 3033 | Jens-Peter Mosemann | 2 | 2 | 7 | 2 | 0.11 |
| 3034 | Michael Reyes | 2 | 2 | 7 | 2 | 0.11 |
| 3035 | Michael Rivera | 2 | 2 | 7 | 2 | 0.11 |
| 3036 | Tymon Miszta | 2 | 2 | 7 | 2 | 0.11 |
| 3037 | Crystal Morse | 1 | 1 | 18 | 8 | 0.11 |
| 3038 | Erik Tucker | 1 | 1 | 18 | 8 | 0.11 |
| 3039 | Juan Qian | 2 | 2 | 14 | 0 | 0.11 |
| 3040 | Sean Mcconnell | 2 | 2 | 14 | 0 | 0.11 |
| 3041 | Wei Fan | 2 | 2 | 14 | 0 | 0.11 |
| 3042 | Bruce Long | 2 | 2 | 10 | 1 | 0.11 |
| 3043 | Curtis Doyle | 2 | 2 | 10 | 1 | 0.11 |
| 3044 | Cynthia Monroe | 2 | 2 | 10 | 1 | 0.11 |
| 3045 | Céline Guérin | 2 | 2 | 10 | 1 | 0.11 |
| 3046 | Debbie Mcgrath | 2 | 2 | 10 | 1 | 0.11 |
| 3047 | Diana Elliott | 2 | 2 | 10 | 1 | 0.11 |
| 3048 | Dorota Cierpka | 2 | 2 | 10 | 1 | 0.11 |
| 3049 | François Coste-Daniel | 2 | 2 | 10 | 1 | 0.11 |
| 3050 | Gail Nguyen | 2 | 2 | 10 | 1 | 0.11 |
| 3051 | Hanako Yamaguchi | 2 | 2 | 10 | 1 | 0.11 |
| 3052 | Jamie Roberts | 2 | 2 | 10 | 1 | 0.11 |
| 3053 | Jeffrey Medina | 2 | 2 | 10 | 1 | 0.11 |
| 3054 | Jing Liang | 2 | 2 | 10 | 1 | 0.11 |
| 3055 | Joy Blanchard | 2 | 2 | 10 | 1 | 0.11 |
| 3056 | Juan Deng | 2 | 2 | 10 | 1 | 0.11 |
| 3057 | Li Xiong | 2 | 2 | 10 | 1 | 0.11 |
| 3058 | Margaux Mathieu | 2 | 2 | 10 | 1 | 0.11 |
| 3059 | Mary Barnes | 2 | 2 | 10 | 1 | 0.11 |
| 3060 | Melissa Williams | 2 | 2 | 10 | 1 | 0.11 |
| 3061 | Ming Lin | 2 | 2 | 10 | 1 | 0.11 |
| 3062 | Noah Frazier Jr. | 2 | 2 | 10 | 1 | 0.11 |
| 3063 | Olav Mülichen | 2 | 2 | 10 | 1 | 0.11 |
| 3064 | Stephanie Horton | 2 | 2 | 10 | 1 | 0.11 |
| 3065 | Theresa Lopez | 2 | 2 | 10 | 1 | 0.11 |
| 3066 | Yan Ye | 2 | 2 | 10 | 1 | 0.11 |
| 3067 | Élisabeth Lemoine | 2 | 2 | 10 | 1 | 0.11 |
| 3068 | Adam Carpenter | 2 | 2 | 6 | 2 | 0.11 |
| 3069 | Adam Lopez | 2 | 2 | 6 | 2 | 0.11 |
| 3070 | Alex Parrish | 2 | 2 | 6 | 2 | 0.11 |
| 3071 | Andrea Crawford | 2 | 2 | 6 | 2 | 0.11 |
| 3072 | Anthony Salas | 2 | 2 | 6 | 2 | 0.11 |
| 3073 | Benvenuto Lerner | 2 | 2 | 6 | 2 | 0.11 |
| 3074 | Cecilia Cusano-Squarcione | 2 | 2 | 6 | 2 | 0.11 |
| 3075 | Daniel Nelson | 2 | 2 | 6 | 2 | 0.11 |
| 3076 | Donald Davis | 2 | 2 | 6 | 2 | 0.11 |
| 3077 | Emily Brooks | 2 | 2 | 6 | 2 | 0.11 |
| 3078 | Eric Wright | 2 | 2 | 6 | 2 | 0.11 |
| 3079 | Frank Bonilla | 2 | 2 | 6 | 2 | 0.11 |
| 3080 | Gianpaolo Sibilia | 2 | 2 | 6 | 2 | 0.11 |
| 3081 | Giovanni Sauer | 2 | 2 | 6 | 2 | 0.11 |
| 3082 | Guido Dobes | 2 | 2 | 6 | 2 | 0.11 |
| 3083 | Holger Hiller | 2 | 2 | 6 | 2 | 0.11 |
| 3084 | Jennifer Smith | 2 | 2 | 6 | 2 | 0.11 |
| 3085 | Kristi Yu | 2 | 2 | 6 | 2 | 0.11 |
| 3086 | Kyle Anderson | 2 | 2 | 6 | 2 | 0.11 |
| 3087 | Nicole Williamson | 2 | 2 | 6 | 2 | 0.11 |
| 3088 | Phillip Hampton | 2 | 2 | 6 | 2 | 0.11 |
| 3089 | Richard Obrien | 2 | 2 | 6 | 2 | 0.11 |
| 3090 | Shelby Kelly | 2 | 2 | 6 | 2 | 0.11 |
| 3091 | Wally Beckmann | 2 | 2 | 6 | 2 | 0.11 |
| 3092 | Wesley Walker | 2 | 2 | 6 | 2 | 0.11 |
| 3093 | Chao Deng | 1 | 1 | 28 | 5 | 0.11 |
| 3094 | Grace Duncan | 1 | 1 | 28 | 5 | 0.11 |
| 3095 | Ming Fu | 1 | 1 | 28 | 5 | 0.11 |
| 3096 | Stephanie Wilkerson | 1 | 1 | 28 | 5 | 0.11 |
| 3097 | Ashley Guzman | 2 | 2 | 13 | 0 | 0.11 |
| 3098 | Guiying Wu | 2 | 2 | 13 | 0 | 0.11 |
| 3099 | Jie Ren | 2 | 2 | 13 | 0 | 0.11 |
| 3100 | Qiang Long | 2 | 1 | 19 | 3 | 0.11 |
| 3101 | Adam de Vries | 1 | 1 | 24 | 6 | 0.11 |
| 3102 | Ana Gonzales | 1 | 1 | 24 | 6 | 0.11 |
| 3103 | Aylin Sire | 1 | 1 | 24 | 6 | 0.11 |
| 3104 | Calogero Mezzetta | 1 | 1 | 24 | 6 | 0.11 |
| 3105 | Luca Hazenveld | 1 | 1 | 24 | 6 | 0.11 |
| 3106 | Mackenzie Brown | 1 | 1 | 24 | 6 | 0.11 |
| 3107 | Victoria Fletcher | 1 | 1 | 24 | 6 | 0.11 |
| 3108 | Alois Jäntsch-Hecker | 2 | 2 | 9 | 1 | 0.11 |
| 3109 | Amber Huff | 2 | 2 | 9 | 1 | 0.11 |
| 3110 | Chao Dong | 2 | 2 | 9 | 1 | 0.11 |
| 3111 | Dana Ferrell | 2 | 2 | 9 | 1 | 0.11 |
| 3112 | Elizabeth Griffin | 2 | 2 | 9 | 1 | 0.11 |
| 3113 | Jing Gu | 2 | 2 | 9 | 1 | 0.11 |
| 3114 | Kristi Henry | 2 | 2 | 9 | 1 | 0.11 |
| 3115 | Margrit Hiller-Jopich | 2 | 2 | 9 | 1 | 0.11 |
| 3116 | Melissa Wheeler | 2 | 2 | 9 | 1 | 0.11 |
| 3117 | Min Meng | 2 | 2 | 9 | 1 | 0.11 |
| 3118 | Ming Liu | 2 | 2 | 9 | 1 | 0.11 |
| 3119 | Morgan Collins | 2 | 2 | 9 | 1 | 0.11 |
| 3120 | Na Duan | 2 | 2 | 9 | 1 | 0.11 |
| 3121 | Nicolaus Fiebig | 2 | 2 | 9 | 1 | 0.11 |
| 3122 | Qiang Zhong | 2 | 2 | 9 | 1 | 0.11 |
| 3123 | Roger Simmons | 2 | 2 | 9 | 1 | 0.11 |
| 3124 | Sherry Powell | 2 | 2 | 9 | 1 | 0.11 |
| 3125 | Thomas King | 2 | 2 | 9 | 1 | 0.11 |
| 3126 | Wei Shao | 2 | 2 | 9 | 1 | 0.11 |
| 3127 | Yan Qiao | 2 | 2 | 9 | 1 | 0.11 |
| 3128 | Yuki Saito | 2 | 2 | 9 | 1 | 0.11 |
| 3129 | Adrien Techer du Voisin | 2 | 2 | 5 | 2 | 0.10 |
| 3130 | Barbara Smith | 2 | 2 | 5 | 2 | 0.10 |
| 3131 | Bouncy Gong | 2 | 2 | 5 | 2 | 0.10 |
| 3132 | Breanna Wright | 2 | 2 | 5 | 2 | 0.10 |
| 3133 | Carsten Fritsch | 2 | 2 | 5 | 2 | 0.10 |
| 3134 | Cheryl Delgado | 2 | 2 | 5 | 2 | 0.10 |
| 3135 | Christopher Powell | 2 | 2 | 5 | 2 | 0.10 |
| 3136 | Dawn Johnson | 2 | 2 | 5 | 2 | 0.10 |
| 3137 | Eugène Lemaire | 2 | 2 | 5 | 2 | 0.10 |
| 3138 | Franck-Georges Delattre | 2 | 2 | 5 | 2 | 0.10 |
| 3139 | Gang Hou | 2 | 2 | 5 | 2 | 0.10 |
| 3140 | Joseph Jackson | 2 | 2 | 5 | 2 | 0.10 |
| 3141 | Kenneth Armstrong | 2 | 2 | 5 | 2 | 0.10 |
| 3142 | Vittoria Mazzanti | 2 | 2 | 5 | 2 | 0.10 |
| 3143 | Bailey Ewing | 1 | 1 | 27 | 5 | 0.10 |
| 3144 | Billy Green | 1 | 1 | 27 | 5 | 0.10 |
| 3145 | Clayton Harper | 1 | 1 | 27 | 5 | 0.10 |
| 3146 | Emily Black | 1 | 1 | 27 | 5 | 0.10 |
| 3147 | James Price | 1 | 1 | 27 | 5 | 0.10 |
| 3148 | Jennifer Duarte | 1 | 1 | 27 | 5 | 0.10 |
| 3149 | Larry Rogers | 1 | 1 | 27 | 5 | 0.10 |
| 3150 | Charles Jacobs | 2 | 2 | 12 | 0 | 0.10 |
| 3151 | Fang Shi | 2 | 2 | 12 | 0 | 0.10 |
| 3152 | Juan He | 2 | 2 | 12 | 0 | 0.10 |
| 3153 | Lisa Shaffer | 2 | 2 | 12 | 0 | 0.10 |
| 3154 | Ming Han | 2 | 2 | 12 | 0 | 0.10 |
| 3155 | Ming Zeng | 2 | 2 | 12 | 0 | 0.10 |
| 3156 | Qiang Cao | 2 | 2 | 12 | 0 | 0.10 |
| 3157 | Qiang Qin | 2 | 2 | 12 | 0 | 0.10 |
| 3158 | Tao Lin | 2 | 2 | 12 | 0 | 0.10 |
| 3159 | Vitali Rogner | 2 | 2 | 12 | 0 | 0.10 |
| 3160 | Wei Zheng | 2 | 2 | 12 | 0 | 0.10 |
| 3161 | Xia Mao | 2 | 2 | 12 | 0 | 0.10 |
| 3162 | Xia Zhao | 2 | 2 | 12 | 0 | 0.10 |
| 3163 | Yan Yu | 2 | 2 | 12 | 0 | 0.10 |
| 3164 | Yong Hou | 2 | 2 | 12 | 0 | 0.10 |
| 3165 | Yong Qiao | 2 | 2 | 12 | 0 | 0.10 |
| 3166 | Andrew Morrison | 2 | 2 | 8 | 1 | 0.10 |
| 3167 | Billy Thompson | 2 | 2 | 8 | 1 | 0.10 |
| 3168 | Blazing Collective | 2 | 2 | 8 | 1 | 0.10 |
| 3169 | Dana Henk-Bachmann | 2 | 2 | 8 | 1 | 0.10 |
| 3170 | David Flores | 2 | 2 | 8 | 1 | 0.10 |
| 3171 | Hannah Elliott | 2 | 2 | 8 | 1 | 0.10 |
| 3172 | Hüseyin Paffrath | 2 | 2 | 8 | 1 | 0.10 |
| 3173 | James Martinez | 2 | 2 | 8 | 1 | 0.10 |
| 3174 | Jason Weeks | 2 | 2 | 8 | 1 | 0.10 |
| 3175 | Jessica Baxter | 2 | 2 | 8 | 1 | 0.10 |
| 3176 | Jing Lu | 2 | 2 | 8 | 1 | 0.10 |
| 3177 | Justin Wagner | 2 | 2 | 8 | 1 | 0.10 |
| 3178 | Kristiane Stadelmann | 2 | 2 | 8 | 1 | 0.10 |
| 3179 | Michael Aguilar | 2 | 2 | 8 | 1 | 0.10 |
| 3180 | Peter Goodwin | 2 | 2 | 8 | 1 | 0.10 |
| 3181 | Wei Lei | 2 | 2 | 8 | 1 | 0.10 |
| 3182 | Yang Ding | 2 | 2 | 8 | 1 | 0.10 |
| 3183 | Elisabet Manola Aguirre Solís | 2 | 2 | 4 | 2 | 0.10 |
| 3184 | Guy Martel | 2 | 2 | 4 | 2 | 0.10 |
| 3185 | Janet Lewis | 2 | 2 | 4 | 2 | 0.10 |
| 3186 | Lisa Wolfe | 2 | 2 | 4 | 2 | 0.10 |
| 3187 | Satomi Kobayashi | 2 | 2 | 4 | 2 | 0.10 |
| 3188 | Scott Flores | 2 | 2 | 4 | 2 | 0.10 |
| 3189 | Sharon Scott | 2 | 2 | 4 | 2 | 0.10 |
| 3190 | Stephen Obrien | 2 | 2 | 4 | 2 | 0.10 |
| 3191 | Juan Antonio Ferrando-Chico | 1 | 1 | 26 | 5 | 0.10 |
| 3192 | Moisés del Tirado | 1 | 1 | 26 | 5 | 0.10 |
| 3193 | Adah Barad | 1 | 0 | 32 | 8 | 0.10 |
| 3194 | Hridaan Chacko | 1 | 0 | 32 | 8 | 0.10 |
| 3195 | Rania Bahri | 1 | 0 | 32 | 8 | 0.10 |
| 3196 | Bradley Brooks | 2 | 2 | 11 | 0 | 0.10 |
| 3197 | Celestial Ink | 2 | 2 | 11 | 0 | 0.10 |
| 3198 | Fang Xu | 2 | 2 | 11 | 0 | 0.10 |
| 3199 | Hans-Josef Steckel-Harloff | 2 | 2 | 11 | 0 | 0.10 |
| 3200 | Horst-Dieter Schleich | 2 | 2 | 11 | 0 | 0.10 |
| 3201 | Lauren Schmitt | 2 | 2 | 11 | 0 | 0.10 |
| 3202 | Lei Xie | 2 | 2 | 11 | 0 | 0.10 |
| 3203 | Li Zhu | 2 | 2 | 11 | 0 | 0.10 |
| 3204 | Min Cai | 2 | 2 | 11 | 0 | 0.10 |
| 3205 | Xiuying Liao | 2 | 2 | 11 | 0 | 0.10 |
| 3206 | Yang Jin | 2 | 2 | 11 | 0 | 0.10 |
| 3207 | Yong Liang | 2 | 2 | 11 | 0 | 0.10 |
| 3208 | Jonathan Hunter | 1 | 1 | 22 | 6 | 0.10 |
| 3209 | Lisa Henderson | 1 | 1 | 22 | 6 | 0.10 |
| 3210 | Auguste-Alexandre Delattre | 2 | 2 | 7 | 1 | 0.10 |
| 3211 | Baccio Muti | 2 | 2 | 7 | 1 | 0.10 |
| 3212 | Chad Booker | 2 | 2 | 7 | 1 | 0.10 |
| 3213 | Christiane Langlois | 2 | 2 | 7 | 1 | 0.10 |
| 3214 | Franciszek Filusz | 2 | 2 | 7 | 1 | 0.10 |
| 3215 | Gabriel Nash | 2 | 2 | 7 | 1 | 0.10 |
| 3216 | Gerard Hornig | 2 | 2 | 7 | 1 | 0.10 |
| 3217 | Guiying Qiao | 2 | 2 | 7 | 1 | 0.10 |
| 3218 | Ildiko Carsten-Thies | 2 | 2 | 7 | 1 | 0.10 |
| 3219 | Jie Liu | 2 | 2 | 7 | 1 | 0.10 |
| 3220 | Krystyna Lübs | 2 | 2 | 7 | 1 | 0.10 |
| 3221 | Linda Guzman | 2 | 2 | 7 | 1 | 0.10 |
| 3222 | Marcelina Ogłaza | 2 | 2 | 7 | 1 | 0.10 |
| 3223 | Mary Thompson | 2 | 2 | 7 | 1 | 0.10 |
| 3224 | Min Lin | 2 | 2 | 7 | 1 | 0.10 |
| 3225 | Paul Powell | 2 | 2 | 7 | 1 | 0.10 |
| 3226 | Radosław Duszkiewicz | 2 | 2 | 7 | 1 | 0.10 |
| 3227 | Robert Norris | 2 | 2 | 7 | 1 | 0.10 |
| 3228 | Ulrike Ziegert | 2 | 2 | 7 | 1 | 0.10 |
| 3229 | Victoire Morvan | 2 | 2 | 7 | 1 | 0.10 |
| 3230 | Xiulan Cheng | 2 | 2 | 7 | 1 | 0.10 |
| 3231 | Fang Gong | 1 | 1 | 29 | 4 | 0.10 |
| 3232 | Jennifer Rice | 1 | 1 | 29 | 4 | 0.10 |
| 3233 | Jeremiah Love | 2 | 2 | 3 | 2 | 0.10 |
| 3234 | Kimaya Jaggi | 2 | 2 | 3 | 2 | 0.10 |
| 3235 | Marisa Tresoldi | 2 | 2 | 3 | 2 | 0.10 |
| 3236 | Miki Hasegawa | 2 | 2 | 3 | 2 | 0.10 |
| 3237 | Miki Miura | 2 | 2 | 3 | 2 | 0.10 |
| 3238 | Miłosz Staciwa | 2 | 2 | 3 | 2 | 0.10 |
| 3239 | Shlok Desai | 2 | 2 | 3 | 2 | 0.10 |
| 3240 | Vanessa Trevisani | 2 | 2 | 3 | 2 | 0.10 |
| 3241 | Velvet Prism | 2 | 2 | 3 | 2 | 0.10 |
| 3242 | Victoria Carpaccio | 2 | 2 | 3 | 2 | 0.10 |
| 3243 | Gang Su | 2 | 1 | 20 | 2 | 0.10 |
| 3244 | Jennifer Faust | 1 | 1 | 25 | 5 | 0.10 |
| 3245 | Wieland Käster | 1 | 1 | 25 | 5 | 0.10 |
| 3246 | Chao Lin | 2 | 2 | 10 | 0 | 0.10 |
| 3247 | Divit Srinivas | 2 | 2 | 10 | 0 | 0.10 |
| 3248 | Fang Xia | 2 | 2 | 10 | 0 | 0.10 |
| 3249 | Guiying Liu | 2 | 2 | 10 | 0 | 0.10 |
| 3250 | Guiying Zhao | 2 | 2 | 10 | 0 | 0.10 |
| 3251 | Jing Jiang | 2 | 2 | 10 | 0 | 0.10 |
| 3252 | Kaylee Quinn | 2 | 2 | 10 | 0 | 0.10 |
| 3253 | Kimberly Stewart | 2 | 2 | 10 | 0 | 0.10 |
| 3254 | Na Gao | 2 | 2 | 10 | 0 | 0.10 |
| 3255 | Na Tan | 2 | 2 | 10 | 0 | 0.10 |
| 3256 | Qiang Shao | 2 | 2 | 10 | 0 | 0.10 |
| 3257 | Tao Deng | 2 | 2 | 10 | 0 | 0.10 |
| 3258 | William Rodriguez | 2 | 2 | 10 | 0 | 0.10 |
| 3259 | Yang Dong | 2 | 2 | 10 | 0 | 0.10 |
| 3260 | Aaron Anderson | 1 | 1 | 32 | 3 | 0.10 |
| 3261 | Ashley Myers | 1 | 1 | 32 | 3 | 0.10 |
| 3262 | Curtis Jones | 1 | 1 | 32 | 3 | 0.10 |
| 3263 | David Benson | 1 | 1 | 32 | 3 | 0.10 |
| 3264 | Joshua Rodriguez | 1 | 1 | 32 | 3 | 0.10 |
| 3265 | Robert Gray | 1 | 1 | 32 | 3 | 0.10 |
| 3266 | William Dominguez | 1 | 1 | 32 | 3 | 0.10 |
| 3267 | Yang Xiong | 3 | 1 | 7 | 1 | 0.10 |
| 3268 | Anaya Barman | 2 | 2 | 6 | 1 | 0.10 |
| 3269 | Ann Nielsen | 2 | 2 | 6 | 1 | 0.10 |
| 3270 | Artur Garbacik | 2 | 2 | 6 | 1 | 0.10 |
| 3271 | Brian Contreras | 2 | 2 | 6 | 1 | 0.10 |
| 3272 | Christine Bartlett | 2 | 2 | 6 | 1 | 0.10 |
| 3273 | Colton Dickerson | 2 | 2 | 6 | 1 | 0.10 |
| 3274 | Damini Kata | 2 | 2 | 6 | 1 | 0.10 |
| 3275 | Elijah Smith | 2 | 2 | 6 | 1 | 0.10 |
| 3276 | Emily Nash | 2 | 2 | 6 | 1 | 0.10 |
| 3277 | Igor Goliasz | 2 | 2 | 6 | 1 | 0.10 |
| 3278 | Jivika Mahal | 2 | 2 | 6 | 1 | 0.10 |
| 3279 | Konrad Klinkosz | 2 | 2 | 6 | 1 | 0.10 |
| 3280 | Laura Beck | 2 | 2 | 6 | 1 | 0.10 |
| 3281 | Lei Li | 2 | 2 | 6 | 1 | 0.10 |
| 3282 | Lindsay Williams | 2 | 2 | 6 | 1 | 0.10 |
| 3283 | Margaud Morel | 2 | 2 | 6 | 1 | 0.10 |
| 3284 | Mary Maxwell | 2 | 2 | 6 | 1 | 0.10 |
| 3285 | Michelle Stafford | 2 | 2 | 6 | 1 | 0.10 |
| 3286 | Nicole Cook | 2 | 2 | 6 | 1 | 0.10 |
| 3287 | Noor van Hoevel en van Zwindrecht | 2 | 2 | 6 | 1 | 0.10 |
| 3288 | Patricia Myers | 2 | 2 | 6 | 1 | 0.10 |
| 3289 | Przemysław Szałkiewicz | 2 | 2 | 6 | 1 | 0.10 |
| 3290 | Richard Goodman | 2 | 2 | 6 | 1 | 0.10 |
| 3291 | Ryan Lin | 2 | 2 | 6 | 1 | 0.10 |
| 3292 | Shelly Kelly | 2 | 2 | 6 | 1 | 0.10 |
| 3293 | Yésica de Oller | 2 | 2 | 6 | 1 | 0.10 |
| 3294 | Anita Parada | 1 | 1 | 17 | 7 | 0.10 |
| 3295 | Larry Massey | 1 | 1 | 28 | 4 | 0.10 |
| 3296 | Raymond Kennedy | 1 | 1 | 28 | 4 | 0.10 |
| 3297 | Rene Wulff-Kranz | 1 | 1 | 28 | 4 | 0.10 |
| 3298 | Andrew Richard | 2 | 2 | 2 | 2 | 0.10 |
| 3299 | Jeremi Wita | 2 | 2 | 2 | 2 | 0.10 |
| 3300 | Phillip Hamilton | 2 | 2 | 2 | 2 | 0.10 |
| 3301 | Sonia Krochmal | 2 | 2 | 2 | 2 | 0.10 |
| 3302 | Sébastien Delaunay | 2 | 2 | 2 | 2 | 0.10 |
| 3303 | Michael Price | 2 | 1 | 19 | 2 | 0.10 |
| 3304 | Edwin Hansen | 2 | 2 | 9 | 0 | 0.10 |
| 3305 | Guiying Yang | 2 | 2 | 9 | 0 | 0.10 |
| 3306 | Jie Song | 2 | 2 | 9 | 0 | 0.10 |
| 3307 | Juan Dai | 2 | 2 | 9 | 0 | 0.10 |
| 3308 | Karl-Friedrich Kreusel | 2 | 2 | 9 | 0 | 0.10 |
| 3309 | Na Tian | 2 | 2 | 9 | 0 | 0.10 |
| 3310 | Na Xiang | 2 | 2 | 9 | 0 | 0.10 |
| 3311 | Ping Chang | 2 | 2 | 9 | 0 | 0.10 |
| 3312 | Wei Bai | 2 | 2 | 9 | 0 | 0.10 |
| 3313 | Wei Kong | 2 | 2 | 9 | 0 | 0.10 |
| 3314 | Xiuying Long | 2 | 2 | 9 | 0 | 0.10 |
| 3315 | Xiuying Shi | 2 | 2 | 9 | 0 | 0.10 |
| 3316 | Yan Hao | 2 | 2 | 9 | 0 | 0.10 |
| 3317 | Yan Ren | 2 | 2 | 9 | 0 | 0.10 |
| 3318 | Yang Song | 2 | 2 | 9 | 0 | 0.10 |
| 3319 | Ella Parker | 3 | 1 | 6 | 1 | 0.10 |
| 3320 | Aarav Chana | 2 | 2 | 5 | 1 | 0.10 |
| 3321 | Alfredo Cases Gaya | 2 | 2 | 5 | 1 | 0.10 |
| 3322 | Arnav Khosla | 2 | 2 | 5 | 1 | 0.10 |
| 3323 | Brandon Roman | 2 | 2 | 5 | 1 | 0.10 |
| 3324 | Carol Moyer | 2 | 2 | 5 | 1 | 0.10 |
| 3325 | Cengiz Knappe | 2 | 2 | 5 | 1 | 0.10 |
| 3326 | Cheryl Malone | 2 | 2 | 5 | 1 | 0.10 |
| 3327 | Christopher Long | 2 | 2 | 5 | 1 | 0.10 |
| 3328 | Cristina Marenzio | 2 | 2 | 5 | 1 | 0.10 |
| 3329 | Gregory Hartman | 2 | 2 | 5 | 1 | 0.10 |
| 3330 | Isa Balotelli | 2 | 2 | 5 | 1 | 0.10 |
| 3331 | Jason Green | 2 | 2 | 5 | 1 | 0.10 |
| 3332 | Jun Bai | 2 | 2 | 5 | 1 | 0.10 |
| 3333 | Kayla Smith | 2 | 2 | 5 | 1 | 0.10 |
| 3334 | Kaylee Patrick | 2 | 2 | 5 | 1 | 0.10 |
| 3335 | Kerri Castillo | 2 | 2 | 5 | 1 | 0.10 |
| 3336 | Marianna Polaszek | 2 | 2 | 5 | 1 | 0.10 |
| 3337 | Mary Campbell | 2 | 2 | 5 | 1 | 0.10 |
| 3338 | Meredith Sullivan | 2 | 2 | 5 | 1 | 0.10 |
| 3339 | Neon Pulse | 2 | 2 | 5 | 1 | 0.10 |
| 3340 | Raghav Chawla | 2 | 2 | 5 | 1 | 0.10 |
| 3341 | Ranbir Sangha | 2 | 2 | 5 | 1 | 0.10 |
| 3342 | Reyansh Bir | 2 | 2 | 5 | 1 | 0.10 |
| 3343 | Rouven Ernst | 2 | 2 | 5 | 1 | 0.10 |
| 3344 | Silent Horizon | 2 | 2 | 5 | 1 | 0.10 |
| 3345 | Sotaro Ito | 2 | 2 | 5 | 1 | 0.10 |
| 3346 | Tyler Watson | 2 | 2 | 5 | 1 | 0.10 |
| 3347 | Vidur D’Alia | 2 | 2 | 5 | 1 | 0.10 |
| 3348 | Walfried Ernst | 2 | 2 | 5 | 1 | 0.10 |
| 3349 | William Alexander | 2 | 2 | 5 | 1 | 0.10 |
| 3350 | Étienne Bruneau | 2 | 2 | 5 | 1 | 0.10 |
| 3351 | Xia Jiang | 2 | 1 | 22 | 1 | 0.10 |
| 3352 | Anthony Beck | 1 | 1 | 16 | 7 | 0.10 |
| 3353 | Kari Barnes | 1 | 1 | 16 | 7 | 0.10 |
| 3354 | Kimberly Gross | 1 | 1 | 16 | 7 | 0.10 |
| 3355 | Nadine Eberhardt | 1 | 1 | 27 | 4 | 0.10 |
| 3356 | Chao Tao | 2 | 1 | 18 | 2 | 0.10 |
| 3357 | Christopher Evans | 1 | 1 | 23 | 5 | 0.10 |
| 3358 | Emmi Biggen | 1 | 1 | 23 | 5 | 0.10 |
| 3359 | Johanna Hauffer | 1 | 1 | 23 | 5 | 0.10 |
| 3360 | Maike Trubin | 1 | 1 | 23 | 5 | 0.10 |
| 3361 | Carol Reid | 2 | 2 | 8 | 0 | 0.10 |
| 3362 | Chad Marks | 2 | 2 | 8 | 0 | 0.10 |
| 3363 | Erik Harris | 2 | 2 | 8 | 0 | 0.10 |
| 3364 | Gang Kong | 2 | 2 | 8 | 0 | 0.10 |
| 3365 | Jing Wu | 2 | 2 | 8 | 0 | 0.10 |
| 3366 | Juan Wang | 2 | 2 | 8 | 0 | 0.10 |
| 3367 | Liwia Piejko | 2 | 2 | 8 | 0 | 0.10 |
| 3368 | Nicolas Blanc | 2 | 2 | 8 | 0 | 0.10 |
| 3369 | Richard Rodriguez | 2 | 2 | 8 | 0 | 0.10 |
| 3370 | Ryohei Ito | 2 | 2 | 8 | 0 | 0.10 |
| 3371 | Stéphane Hernandez | 2 | 2 | 8 | 0 | 0.10 |
| 3372 | The Nulls | 2 | 2 | 8 | 0 | 0.10 |
| 3373 | Xia Xiao | 2 | 2 | 8 | 0 | 0.10 |
| 3374 | Yan Gu | 2 | 2 | 8 | 0 | 0.10 |
| 3375 | Zoé Roux | 2 | 2 | 8 | 0 | 0.10 |
| 3376 | Élisabeth Vasseur | 2 | 2 | 8 | 0 | 0.10 |
| 3377 | Adam Arnold | 1 | 1 | 30 | 3 | 0.10 |
| 3378 | Carlos Townsend | 1 | 1 | 30 | 3 | 0.10 |
| 3379 | Dustin Lopez | 2 | 2 | 4 | 1 | 0.10 |
| 3380 | Emily Raymond | 2 | 2 | 4 | 1 | 0.10 |
| 3381 | Gabriel Barr | 2 | 2 | 4 | 1 | 0.10 |
| 3382 | Ida Lachmann | 2 | 2 | 4 | 1 | 0.10 |
| 3383 | Isabell Berger | 2 | 2 | 4 | 1 | 0.10 |
| 3384 | Jason Brown | 2 | 2 | 4 | 1 | 0.10 |
| 3385 | Juan Guo | 2 | 2 | 4 | 1 | 0.10 |
| 3386 | Justin Thomas | 2 | 2 | 4 | 1 | 0.10 |
| 3387 | Kathleen Harvey | 2 | 2 | 4 | 1 | 0.10 |
| 3388 | Latoya English | 2 | 2 | 4 | 1 | 0.10 |
| 3389 | Laura Anderson | 2 | 2 | 4 | 1 | 0.10 |
| 3390 | Leonard Phillips | 2 | 2 | 4 | 1 | 0.10 |
| 3391 | Lise Gerrits | 2 | 2 | 4 | 1 | 0.10 |
| 3392 | Matthew Gallagher | 2 | 2 | 4 | 1 | 0.10 |
| 3393 | Matthew Nichols | 2 | 2 | 4 | 1 | 0.10 |
| 3394 | Matthew Robertson | 2 | 2 | 4 | 1 | 0.10 |
| 3395 | Michael French | 2 | 2 | 4 | 1 | 0.10 |
| 3396 | Michelle Smith | 2 | 2 | 4 | 1 | 0.10 |
| 3397 | Nikola Nerger | 2 | 2 | 4 | 1 | 0.10 |
| 3398 | Seth Duncan | 2 | 2 | 4 | 1 | 0.10 |
| 3399 | Siglinde Ruppersberger | 2 | 2 | 4 | 1 | 0.10 |
| 3400 | Walter Bell | 2 | 2 | 4 | 1 | 0.10 |
| 3401 | Wei Yi | 2 | 2 | 4 | 1 | 0.10 |
| 3402 | Yang Tan | 2 | 2 | 4 | 1 | 0.10 |
| 3403 | Yong Liu | 2 | 2 | 4 | 1 | 0.10 |
| 3404 | Brandy Reyes | 1 | 1 | 26 | 4 | 0.10 |
| 3405 | Dennis Wood | 1 | 1 | 26 | 4 | 0.10 |
| 3406 | Justin Kirk | 1 | 1 | 26 | 4 | 0.10 |
| 3407 | Laura Gibbs | 1 | 1 | 26 | 4 | 0.10 |
| 3408 | Mary Medina | 1 | 1 | 26 | 4 | 0.10 |
| 3409 | Pamela Miller | 1 | 1 | 26 | 4 | 0.10 |
| 3410 | Peter Vega | 1 | 1 | 26 | 4 | 0.10 |
| 3411 | Raymond Mccoy | 1 | 1 | 26 | 4 | 0.10 |
| 3412 | Rhonda Brown | 1 | 1 | 26 | 4 | 0.10 |
| 3413 | Yong Shao | 2 | 1 | 17 | 2 | 0.10 |
| 3414 | Gabriel Olson | 1 | 1 | 22 | 5 | 0.10 |
| 3415 | James Stevens | 1 | 1 | 22 | 5 | 0.10 |
| 3416 | Jeremy Little | 1 | 1 | 22 | 5 | 0.10 |
| 3417 | Yong Song | 1 | 1 | 22 | 5 | 0.10 |
| 3418 | Bertrand-Robert Duval | 2 | 2 | 7 | 0 | 0.10 |
| 3419 | Dustin Newman | 2 | 2 | 7 | 0 | 0.10 |
| 3420 | Edward Jacobs | 2 | 2 | 7 | 0 | 0.10 |
| 3421 | Eleanora Bersani | 2 | 2 | 7 | 0 | 0.10 |
| 3422 | Elizabeth Garcia | 2 | 2 | 7 | 0 | 0.10 |
| 3423 | Fang Fu | 2 | 2 | 7 | 0 | 0.10 |
| 3424 | Fang Hu | 2 | 2 | 7 | 0 | 0.10 |
| 3425 | Fang Luo | 2 | 2 | 7 | 0 | 0.10 |
| 3426 | Fang Yu | 2 | 2 | 7 | 0 | 0.10 |
| 3427 | Hector Davis | 2 | 2 | 7 | 0 | 0.10 |
| 3428 | Jie Meng | 2 | 2 | 7 | 0 | 0.10 |
| 3429 | Jing Xiao | 2 | 2 | 7 | 0 | 0.10 |
| 3430 | Juan Wan | 2 | 2 | 7 | 0 | 0.10 |
| 3431 | Kevin Burch | 2 | 2 | 7 | 0 | 0.10 |
| 3432 | Kimberly Moore | 2 | 2 | 7 | 0 | 0.10 |
| 3433 | Li Qian | 2 | 2 | 7 | 0 | 0.10 |
| 3434 | Li Tao | 2 | 2 | 7 | 0 | 0.10 |
| 3435 | Roger Orozco | 2 | 2 | 7 | 0 | 0.10 |
| 3436 | Tao Tao | 2 | 2 | 7 | 0 | 0.10 |
| 3437 | Timothy Moore | 2 | 2 | 7 | 0 | 0.10 |
| 3438 | William Brown | 2 | 2 | 7 | 0 | 0.10 |
| 3439 | Xia Wei | 2 | 2 | 7 | 0 | 0.10 |
| 3440 | Yong Zhou | 2 | 2 | 7 | 0 | 0.10 |
| 3441 | Mark Garcia | 2 | 1 | 13 | 3 | 0.10 |
| 3442 | Shannon Smith | 2 | 1 | 13 | 3 | 0.10 |
| 3443 | Adriano Tomei | 2 | 2 | 3 | 1 | 0.10 |
| 3444 | Aniela Wszoła | 2 | 2 | 3 | 1 | 0.10 |
| 3445 | Becky Walters | 2 | 2 | 3 | 1 | 0.10 |
| 3446 | Bernard-André Rolland | 2 | 2 | 3 | 1 | 0.10 |
| 3447 | Brad Martinez | 2 | 2 | 3 | 1 | 0.10 |
| 3448 | Brandon Hoffman | 2 | 2 | 3 | 1 | 0.10 |
| 3449 | Christelle Grégoire | 2 | 2 | 3 | 1 | 0.10 |
| 3450 | Daniel Smith | 2 | 2 | 3 | 1 | 0.10 |
| 3451 | Devansh Divan | 2 | 2 | 3 | 1 | 0.10 |
| 3452 | Elwira Heuser | 2 | 2 | 3 | 1 | 0.10 |
| 3453 | Fateh Dube | 2 | 2 | 3 | 1 | 0.10 |
| 3454 | Fiamma Baracca | 2 | 2 | 3 | 1 | 0.10 |
| 3455 | Gary Tucker | 2 | 2 | 3 | 1 | 0.10 |
| 3456 | Holly Love | 2 | 2 | 3 | 1 | 0.10 |
| 3457 | Isabelle Baudry de Michel | 2 | 2 | 3 | 1 | 0.10 |
| 3458 | Jacob Yang | 2 | 2 | 3 | 1 | 0.10 |
| 3459 | Jamie Schmidt | 2 | 2 | 3 | 1 | 0.10 |
| 3460 | Janice Schultz | 2 | 2 | 3 | 1 | 0.10 |
| 3461 | Jonathan Lewis | 2 | 2 | 3 | 1 | 0.10 |
| 3462 | Joseph Chen | 2 | 2 | 3 | 1 | 0.10 |
| 3463 | Joseph Ramirez | 2 | 2 | 3 | 1 | 0.10 |
| 3464 | Kenneth Randolph | 2 | 2 | 3 | 1 | 0.10 |
| 3465 | Larry Walters | 2 | 2 | 3 | 1 | 0.10 |
| 3466 | Laura Stanton | 2 | 2 | 3 | 1 | 0.10 |
| 3467 | Lodovico Interminei | 2 | 2 | 3 | 1 | 0.10 |
| 3468 | Macaria de Landa | 2 | 2 | 3 | 1 | 0.10 |
| 3469 | Mateusz Mikoda | 2 | 2 | 3 | 1 | 0.10 |
| 3470 | Matthew Carter | 2 | 2 | 3 | 1 | 0.10 |
| 3471 | Megan Morrow | 2 | 2 | 3 | 1 | 0.10 |
| 3472 | Misha Batta | 2 | 2 | 3 | 1 | 0.10 |
| 3473 | Robert Lynn | 2 | 2 | 3 | 1 | 0.10 |
| 3474 | Serafina Céspedes Sales | 2 | 2 | 3 | 1 | 0.10 |
| 3475 | Sherry Hernandez | 2 | 2 | 3 | 1 | 0.10 |
| 3476 | Sumer Kakar | 2 | 2 | 3 | 1 | 0.10 |
| 3477 | Timothy Riley | 2 | 2 | 3 | 1 | 0.10 |
| 3478 | Tobiasz Haponiuk | 2 | 2 | 3 | 1 | 0.10 |
| 3479 | Phillip Brooks | 2 | 1 | 9 | 4 | 0.10 |
| 3480 | Anna Glass | 1 | 1 | 25 | 4 | 0.10 |
| 3481 | Jamie Terry | 1 | 1 | 25 | 4 | 0.10 |
| 3482 | Kimberly Alvarez | 1 | 1 | 25 | 4 | 0.10 |
| 3483 | Nancy Macias | 1 | 1 | 25 | 4 | 0.10 |
| 3484 | Rebecca Robinson | 1 | 1 | 25 | 4 | 0.10 |
| 3485 | Samuel Thompson | 1 | 1 | 25 | 4 | 0.10 |
| 3486 | Nikolaos Jäkel | 1 | 1 | 21 | 5 | 0.09 |
| 3487 | Biju Swamy | 2 | 2 | 6 | 0 | 0.09 |
| 3488 | Chao Liu | 2 | 2 | 6 | 0 | 0.09 |
| 3489 | Chao Sun | 2 | 2 | 6 | 0 | 0.09 |
| 3490 | Dennis Mcdowell | 2 | 2 | 6 | 0 | 0.09 |
| 3491 | Elakshi Venkataraman | 2 | 2 | 6 | 0 | 0.09 |
| 3492 | Electric Collective | 2 | 2 | 6 | 0 | 0.09 |
| 3493 | Enzio Garibaldi | 2 | 2 | 6 | 0 | 0.09 |
| 3494 | Ethan Clarke | 2 | 2 | 6 | 0 | 0.09 |
| 3495 | Fang Mo | 2 | 2 | 6 | 0 | 0.09 |
| 3496 | Gabrielle Richardson | 2 | 2 | 6 | 0 | 0.09 |
| 3497 | Gang Deng | 2 | 2 | 6 | 0 | 0.09 |
| 3498 | Heidi Allen | 2 | 2 | 6 | 0 | 0.09 |
| 3499 | Jason Warner | 2 | 2 | 6 | 0 | 0.09 |
| 3500 | Jeffrey Watson | 2 | 2 | 6 | 0 | 0.09 |
| 3501 | Jing Dai | 2 | 2 | 6 | 0 | 0.09 |
| 3502 | Jing Dong | 2 | 2 | 6 | 0 | 0.09 |
| 3503 | Jing Yao | 2 | 2 | 6 | 0 | 0.09 |
| 3504 | Jonathan Marquez | 2 | 2 | 6 | 0 | 0.09 |
| 3505 | Juan Hall | 2 | 2 | 6 | 0 | 0.09 |
| 3506 | Jun Zeng | 2 | 2 | 6 | 0 | 0.09 |
| 3507 | Kara Lee | 2 | 2 | 6 | 0 | 0.09 |
| 3508 | Keya Kota | 2 | 2 | 6 | 0 | 0.09 |
| 3509 | Li Pan | 2 | 2 | 6 | 0 | 0.09 |
| 3510 | Lori Henderson | 2 | 2 | 6 | 0 | 0.09 |
| 3511 | Margaret Mccarthy | 2 | 2 | 6 | 0 | 0.09 |
| 3512 | Min Gu | 2 | 2 | 6 | 0 | 0.09 |
| 3513 | Min Tian | 2 | 2 | 6 | 0 | 0.09 |
| 3514 | Miss Allison King | 2 | 2 | 6 | 0 | 0.09 |
| 3515 | Ping Lu | 2 | 2 | 6 | 0 | 0.09 |
| 3516 | Qiang Tao | 2 | 2 | 6 | 0 | 0.09 |
| 3517 | Qiang Xia | 2 | 2 | 6 | 0 | 0.09 |
| 3518 | Ricciotti Traetta | 2 | 2 | 6 | 0 | 0.09 |
| 3519 | Shaan Jaggi | 2 | 2 | 6 | 0 | 0.09 |
| 3520 | Sophie Bennett | 2 | 2 | 6 | 0 | 0.09 |
| 3521 | Sosimo Donaire Marí | 2 | 2 | 6 | 0 | 0.09 |
| 3522 | Syncopated Symphony Collective | 2 | 2 | 6 | 0 | 0.09 |
| 3523 | Velvet Horizon | 2 | 2 | 6 | 0 | 0.09 |
| 3524 | Wei Zou | 2 | 2 | 6 | 0 | 0.09 |
| 3525 | Xiulan Qiao | 2 | 2 | 6 | 0 | 0.09 |
| 3526 | Xiulan Yu | 2 | 2 | 6 | 0 | 0.09 |
| 3527 | Xiuying Xue | 2 | 2 | 6 | 0 | 0.09 |
| 3528 | Yan Ma | 2 | 2 | 6 | 0 | 0.09 |
| 3529 | Yong Feng | 2 | 2 | 6 | 0 | 0.09 |
| 3530 | Minoru Nakajima | 2 | 1 | 12 | 3 | 0.09 |
| 3531 | Alexander Jenkins | 2 | 2 | 2 | 1 | 0.09 |
| 3532 | Amy Moore | 2 | 2 | 2 | 1 | 0.09 |
| 3533 | Angela Wallace | 2 | 2 | 2 | 1 | 0.09 |
| 3534 | Crossroads & Cipher | 2 | 2 | 2 | 1 | 0.09 |
| 3535 | Daniel Cooper | 2 | 2 | 2 | 1 | 0.09 |
| 3536 | Elizabeth Willis | 2 | 2 | 2 | 1 | 0.09 |
| 3537 | Emily Bush | 2 | 2 | 2 | 1 | 0.09 |
| 3538 | Eric Briggs | 2 | 2 | 2 | 1 | 0.09 |
| 3539 | Francisco Manning | 2 | 2 | 2 | 1 | 0.09 |
| 3540 | Frau Melissa Neuschäfer | 2 | 2 | 2 | 1 | 0.09 |
| 3541 | Gerold Mangold | 2 | 2 | 2 | 1 | 0.09 |
| 3542 | Jason Singleton | 2 | 2 | 2 | 1 | 0.09 |
| 3543 | Kimberly Rodriguez | 2 | 2 | 2 | 1 | 0.09 |
| 3544 | Mandy Murphy | 2 | 2 | 2 | 1 | 0.09 |
| 3545 | Margrit Stiffel | 2 | 2 | 2 | 1 | 0.09 |
| 3546 | Mary Smith | 2 | 2 | 2 | 1 | 0.09 |
| 3547 | Melissa Thomas | 2 | 2 | 2 | 1 | 0.09 |
| 3548 | Melissa Wilson | 2 | 2 | 2 | 1 | 0.09 |
| 3549 | Melissa Wyatt | 2 | 2 | 2 | 1 | 0.09 |
| 3550 | Monika Przewłoka | 2 | 2 | 2 | 1 | 0.09 |
| 3551 | Nikolas Naser | 2 | 2 | 2 | 1 | 0.09 |
| 3552 | Norbert Flisek | 2 | 2 | 2 | 1 | 0.09 |
| 3553 | Renato Holsten | 2 | 2 | 2 | 1 | 0.09 |
| 3554 | Seth Payne | 2 | 2 | 2 | 1 | 0.09 |
| 3555 | Stacy Hendricks | 2 | 2 | 2 | 1 | 0.09 |
| 3556 | Stilla Koch | 2 | 2 | 2 | 1 | 0.09 |
| 3557 | The Garage Dolls | 2 | 2 | 2 | 1 | 0.09 |
| 3558 | Walentina Ernst-Klingelhöfer | 2 | 2 | 2 | 1 | 0.09 |
| 3559 | Gwendolyn Fitzgerald | 2 | 1 | 8 | 4 | 0.09 |
| 3560 | Sharon Sanchez | 2 | 1 | 19 | 1 | 0.09 |
| 3561 | Xiulan Jin | 2 | 1 | 19 | 1 | 0.09 |
| 3562 | Christopher Gonzalez | 1 | 1 | 24 | 4 | 0.09 |
| 3563 | Emily Johnson | 1 | 1 | 24 | 4 | 0.09 |
| 3564 | Gary Torres | 1 | 1 | 24 | 4 | 0.09 |
| 3565 | Gregory Porter | 1 | 1 | 24 | 4 | 0.09 |
| 3566 | James Cain | 1 | 1 | 24 | 4 | 0.09 |
| 3567 | Leonard Dudley | 1 | 1 | 24 | 4 | 0.09 |
| 3568 | Lisa Page | 1 | 1 | 24 | 4 | 0.09 |
| 3569 | Patricia Johnson | 1 | 1 | 24 | 4 | 0.09 |
| 3570 | Thomas Mcconnell | 1 | 1 | 24 | 4 | 0.09 |
| 3571 | Xiuying Wen | 1 | 1 | 24 | 4 | 0.09 |
| 3572 | Pamela Johnson | 2 | 1 | 15 | 2 | 0.09 |
| 3573 | Jason Aguirre | 1 | 1 | 20 | 5 | 0.09 |
| 3574 | John Graves | 1 | 1 | 20 | 5 | 0.09 |
| 3575 | Matthew Lane | 1 | 1 | 20 | 5 | 0.09 |
| 3576 | Sheryl Roman | 1 | 1 | 20 | 5 | 0.09 |
| 3577 | Joseph Luna | 3 | 1 | 6 | 0 | 0.09 |
| 3578 | Sylvia Watson | 3 | 1 | 6 | 0 | 0.09 |
| 3579 | Aiden Harper | 2 | 2 | 5 | 0 | 0.09 |
| 3580 | Antonina Zaccardo | 2 | 2 | 5 | 0 | 0.09 |
| 3581 | Balkan Prisms | 2 | 2 | 5 | 0 | 0.09 |
| 3582 | Beth Gray | 2 | 2 | 5 | 0 | 0.09 |
| 3583 | Brandi Riley | 2 | 2 | 5 | 0 | 0.09 |
| 3584 | Brita Holsten | 2 | 2 | 5 | 0 | 0.09 |
| 3585 | Chao Zou | 2 | 2 | 5 | 0 | 0.09 |
| 3586 | Fang Wen | 2 | 2 | 5 | 0 | 0.09 |
| 3587 | Finn Morgan | 2 | 2 | 5 | 0 | 0.09 |
| 3588 | Frank Johnson | 2 | 2 | 5 | 0 | 0.09 |
| 3589 | Heinz-Gerd Klapp | 2 | 2 | 5 | 0 | 0.09 |
| 3590 | Highway Vibes | 2 | 2 | 5 | 0 | 0.09 |
| 3591 | Jessica Lewis | 2 | 2 | 5 | 0 | 0.09 |
| 3592 | Jing Xia | 2 | 2 | 5 | 0 | 0.09 |
| 3593 | Jing Zhao | 2 | 2 | 5 | 0 | 0.09 |
| 3594 | Johnathan Sanchez | 2 | 2 | 5 | 0 | 0.09 |
| 3595 | Kinship Harmony | 2 | 2 | 5 | 0 | 0.09 |
| 3596 | Lei Su | 2 | 2 | 5 | 0 | 0.09 |
| 3597 | Lidia Battisti-Righi | 2 | 2 | 5 | 0 | 0.09 |
| 3598 | Marianela Vila Zaragoza | 2 | 2 | 5 | 0 | 0.09 |
| 3599 | Megan Baird | 2 | 2 | 5 | 0 | 0.09 |
| 3600 | Michael Peterson | 2 | 2 | 5 | 0 | 0.09 |
| 3601 | Rita Finzi | 2 | 2 | 5 | 0 | 0.09 |
| 3602 | Romana Iadanza | 2 | 2 | 5 | 0 | 0.09 |
| 3603 | Skylar Brooks | 2 | 2 | 5 | 0 | 0.09 |
| 3604 | Steven Boyd | 2 | 2 | 5 | 0 | 0.09 |
| 3605 | Tao Luo | 2 | 2 | 5 | 0 | 0.09 |
| 3606 | Xavier Gaillard | 2 | 2 | 5 | 0 | 0.09 |
| 3607 | Xiulan Wan | 2 | 2 | 5 | 0 | 0.09 |
| 3608 | Alicia Robertson | 1 | 1 | 16 | 6 | 0.09 |
| 3609 | Amanda Ochoa | 2 | 2 | 1 | 1 | 0.09 |
| 3610 | Blake Rodriguez | 2 | 2 | 1 | 1 | 0.09 |
| 3611 | Bryan Sanchez | 2 | 2 | 1 | 1 | 0.09 |
| 3612 | Carrie Martin | 2 | 2 | 1 | 1 | 0.09 |
| 3613 | Charles Wallace | 2 | 2 | 1 | 1 | 0.09 |
| 3614 | Concetta Klotz | 2 | 2 | 1 | 1 | 0.09 |
| 3615 | Douglas Lewis | 2 | 2 | 1 | 1 | 0.09 |
| 3616 | Elizabeth Cochran PhD | 2 | 2 | 1 | 1 | 0.09 |
| 3617 | Evelien Becht-Versluijs | 2 | 2 | 1 | 1 | 0.09 |
| 3618 | Nanami Watanabe | 2 | 2 | 1 | 1 | 0.09 |
| 3619 | Navya Rana | 2 | 2 | 1 | 1 | 0.09 |
| 3620 | Ronald Brooks | 2 | 2 | 1 | 1 | 0.09 |
| 3621 | Sophia Dippel | 2 | 2 | 1 | 1 | 0.09 |
| 3622 | Susan Willis | 2 | 2 | 1 | 1 | 0.09 |
| 3623 | Whitney Taylor | 2 | 2 | 1 | 1 | 0.09 |
| 3624 | Yoichi Sato | 2 | 2 | 1 | 1 | 0.09 |
| 3625 | Yvonne Alexander | 2 | 2 | 1 | 1 | 0.09 |
| 3626 | Zeeshan Dora | 2 | 2 | 1 | 1 | 0.09 |
| 3627 | Éric Daniel | 2 | 2 | 1 | 1 | 0.09 |
| 3628 | Adrien Weiss | 1 | 1 | 23 | 4 | 0.09 |
| 3629 | Charles du Perez | 1 | 1 | 23 | 4 | 0.09 |
| 3630 | Damon Stewart | 1 | 1 | 23 | 4 | 0.09 |
| 3631 | Pauline Guyot de la Maillet | 1 | 1 | 23 | 4 | 0.09 |
| 3632 | Ryohei Sato | 1 | 1 | 23 | 4 | 0.09 |
| 3633 | Steve Washington | 1 | 1 | 23 | 4 | 0.09 |
| 3634 | James Thomas | 1 | 1 | 19 | 5 | 0.09 |
| 3635 | Thomas Bradley | 1 | 1 | 19 | 5 | 0.09 |
| 3636 | Xia Kong | 1 | 1 | 19 | 5 | 0.09 |
| 3637 | Baudelio Anglada-Valenzuela | 2 | 2 | 4 | 0 | 0.09 |
| 3638 | Charles Delaunay | 2 | 2 | 4 | 0 | 0.09 |
| 3639 | Elizabeth Mccarthy | 2 | 2 | 4 | 0 | 0.09 |
| 3640 | Hans-Josef Killer | 2 | 2 | 4 | 0 | 0.09 |
| 3641 | James Williams | 2 | 2 | 4 | 0 | 0.09 |
| 3642 | Kerri Weeks | 2 | 2 | 4 | 0 | 0.09 |
| 3643 | Lauren Foster | 2 | 2 | 4 | 0 | 0.09 |
| 3644 | Lauren Powell | 2 | 2 | 4 | 0 | 0.09 |
| 3645 | Louis Armstrong | 2 | 2 | 4 | 0 | 0.09 |
| 3646 | Marc Raymond | 2 | 2 | 4 | 0 | 0.09 |
| 3647 | Miloš Pokorný | 2 | 2 | 4 | 0 | 0.09 |
| 3648 | Mirja Jacob | 2 | 2 | 4 | 0 | 0.09 |
| 3649 | Mohamed Sastre Godoy | 2 | 2 | 4 | 0 | 0.09 |
| 3650 | N.V. Blake | 2 | 2 | 4 | 0 | 0.09 |
| 3651 | Prudencio Nilo Arjona Huguet | 2 | 2 | 4 | 0 | 0.09 |
| 3652 | Sahil Khalsa | 2 | 2 | 4 | 0 | 0.09 |
| 3653 | Wei Wei | 2 | 2 | 4 | 0 | 0.09 |
| 3654 | Knarren | 2 | 1 | 10 | 3 | 0.09 |
| 3655 | Angela Thompson | 2 | 1 | 17 | 1 | 0.09 |
| 3656 | Cynthia Nunez | 2 | 1 | 17 | 1 | 0.09 |
| 3657 | Veronica Ferguson | 2 | 1 | 17 | 1 | 0.09 |
| 3658 | Friedl Bauer-Hövel | 1 | 1 | 22 | 4 | 0.09 |
| 3659 | Hartmut Ruppert | 1 | 1 | 22 | 4 | 0.09 |
| 3660 | Heiderose Putz | 1 | 1 | 22 | 4 | 0.09 |
| 3661 | Herr Hans Dieter Hentschel | 1 | 1 | 22 | 4 | 0.09 |
| 3662 | Hertha Schinke | 1 | 1 | 22 | 4 | 0.09 |
| 3663 | Shray Agarwal | 1 | 1 | 7 | 8 | 0.09 |
| 3664 | Kimberly Estrada | 1 | 1 | 18 | 5 | 0.09 |
| 3665 | Édouard-Rémy Clerc | 1 | 1 | 18 | 5 | 0.09 |
| 3666 | Lucas Bennett | 3 | 1 | 4 | 0 | 0.09 |
| 3667 | Maya Torres | 3 | 1 | 4 | 0 | 0.09 |
| 3668 | Olivia Carter | 3 | 1 | 4 | 0 | 0.09 |
| 3669 | Ashley Brooks | 2 | 2 | 3 | 0 | 0.09 |
| 3670 | Bethany Jennings | 2 | 2 | 3 | 0 | 0.09 |
| 3671 | Brittany Harvey | 2 | 2 | 3 | 0 | 0.09 |
| 3672 | Carlos Duffy | 2 | 2 | 3 | 0 | 0.09 |
| 3673 | Colin Wood | 2 | 2 | 3 | 0 | 0.09 |
| 3674 | Elizabeth Parker | 2 | 2 | 3 | 0 | 0.09 |
| 3675 | Herr Folkert Vogt | 2 | 2 | 3 | 0 | 0.09 |
| 3676 | Ivana Vávrová | 2 | 2 | 3 | 0 | 0.09 |
| 3677 | Jie Chen | 2 | 2 | 3 | 0 | 0.09 |
| 3678 | Jun Xue | 2 | 2 | 3 | 0 | 0.09 |
| 3679 | Justin Berry | 2 | 2 | 3 | 0 | 0.09 |
| 3680 | Kathryn Mcknight | 2 | 2 | 3 | 0 | 0.09 |
| 3681 | Lila Rivers | 2 | 2 | 3 | 0 | 0.09 |
| 3682 | Mia Waters | 2 | 2 | 3 | 0 | 0.09 |
| 3683 | Nancy Arnold | 2 | 2 | 3 | 0 | 0.09 |
| 3684 | Ritvik Raman | 2 | 2 | 3 | 0 | 0.09 |
| 3685 | William Knapp | 2 | 2 | 3 | 0 | 0.09 |
| 3686 | Dawid Golda | 1 | 1 | 14 | 6 | 0.09 |
| 3687 | Brandi Noble | 1 | 1 | 25 | 3 | 0.09 |
| 3688 | Hailey Hak | 1 | 1 | 25 | 3 | 0.09 |
| 3689 | Lynn Brumleve-van der Horst | 1 | 1 | 25 | 3 | 0.09 |
| 3690 | Maud van de Pol | 1 | 1 | 25 | 3 | 0.09 |
| 3691 | Mohamed van de Berg | 1 | 1 | 25 | 3 | 0.09 |
| 3692 | Olaf Otto | 1 | 1 | 25 | 3 | 0.09 |
| 3693 | Otmar Fröhlich | 1 | 1 | 25 | 3 | 0.09 |
| 3694 | Richard Sweeney | 1 | 1 | 25 | 3 | 0.09 |
| 3695 | Cody Moore | 2 | 1 | 16 | 1 | 0.09 |
| 3696 | Jacqueline Young | 2 | 1 | 16 | 1 | 0.09 |
| 3697 | John Ray | 2 | 1 | 16 | 1 | 0.09 |
| 3698 | Kyle Hill | 2 | 1 | 16 | 1 | 0.09 |
| 3699 | Kevin Davidson | 1 | 1 | 21 | 4 | 0.09 |
| 3700 | Nicole Clark | 1 | 1 | 21 | 4 | 0.09 |
| 3701 | Alicia Heinz | 2 | 1 | 12 | 2 | 0.09 |
| 3702 | Ilona Stolze | 2 | 1 | 12 | 2 | 0.09 |
| 3703 | Rose-Marie Schmidtke | 2 | 1 | 12 | 2 | 0.09 |
| 3704 | Xiuying Wei | 2 | 1 | 12 | 2 | 0.09 |
| 3705 | Francisco Lyons | 1 | 1 | 17 | 5 | 0.09 |
| 3706 | Hector Porcel Gomis | 1 | 1 | 17 | 5 | 0.09 |
| 3707 | Nicolasa Zaragoza Asenjo | 1 | 1 | 17 | 5 | 0.09 |
| 3708 | Clara Henderson | 2 | 2 | 2 | 0 | 0.09 |
| 3709 | Daniel Aubert-Brunet | 2 | 2 | 2 | 0 | 0.09 |
| 3710 | Ethan Crowley | 2 | 2 | 2 | 0 | 0.09 |
| 3711 | Friedrich-Wilhelm Ullmann | 2 | 2 | 2 | 0 | 0.09 |
| 3712 | Inès-Adèle Valette | 2 | 2 | 2 | 0 | 0.09 |
| 3713 | Jing Wan | 2 | 2 | 2 | 0 | 0.09 |
| 3714 | Mark Beck | 2 | 2 | 2 | 0 | 0.09 |
| 3715 | Mary Brooks | 2 | 2 | 2 | 0 | 0.09 |
| 3716 | Melissa Harris | 2 | 2 | 2 | 0 | 0.09 |
| 3717 | Milo Knight | 2 | 2 | 2 | 0 | 0.09 |
| 3718 | Odette-Inès Lelièvre | 2 | 2 | 2 | 0 | 0.09 |
| 3719 | Renee Lynch | 2 | 2 | 2 | 0 | 0.09 |
| 3720 | Zara Quinn | 2 | 2 | 2 | 0 | 0.09 |
| 3721 | Jie Gao | 1 | 1 | 24 | 3 | 0.09 |
| 3722 | Kara Frazier | 1 | 1 | 24 | 3 | 0.09 |
| 3723 | Andrew Jenkins | 2 | 1 | 15 | 1 | 0.09 |
| 3724 | Matthew Salazar | 2 | 1 | 15 | 1 | 0.09 |
| 3725 | Antonietta Zamengo-Zanazzo | 1 | 1 | 20 | 4 | 0.09 |
| 3726 | Douglas Gonzalez | 1 | 1 | 20 | 4 | 0.09 |
| 3727 | Joseph Beltran | 1 | 1 | 20 | 4 | 0.09 |
| 3728 | Patrizio Antonello-Salvemini | 1 | 1 | 20 | 4 | 0.09 |
| 3729 | Troy Ruiz | 1 | 1 | 20 | 4 | 0.09 |
| 3730 | Charles Mccoy | 1 | 1 | 16 | 5 | 0.09 |
| 3731 | Suhana Din | 1 | 1 | 16 | 5 | 0.09 |
| 3732 | Anya Krishnan | 2 | 2 | 1 | 0 | 0.09 |
| 3733 | Denise Knight | 2 | 2 | 1 | 0 | 0.09 |
| 3734 | Derek Cline | 2 | 2 | 1 | 0 | 0.09 |
| 3735 | Edward Henry | 2 | 2 | 1 | 0 | 0.09 |
| 3736 | Ishita Bahri | 2 | 2 | 1 | 0 | 0.09 |
| 3737 | Krish Wali | 2 | 2 | 1 | 0 | 0.09 |
| 3738 | Melissa Warren | 2 | 2 | 1 | 0 | 0.09 |
| 3739 | Nirvi Chahal | 2 | 2 | 1 | 0 | 0.09 |
| 3740 | Pihu Gulati | 2 | 2 | 1 | 0 | 0.09 |
| 3741 | Siya Sahni | 2 | 2 | 1 | 0 | 0.09 |
| 3742 | Alan Wilson | 1 | 1 | 23 | 3 | 0.09 |
| 3743 | Bradley Wright | 1 | 1 | 23 | 3 | 0.09 |
| 3744 | Douglas Turner | 1 | 1 | 23 | 3 | 0.09 |
| 3745 | Gregory Wright | 1 | 1 | 23 | 3 | 0.09 |
| 3746 | Stephen Ramirez | 1 | 1 | 23 | 3 | 0.09 |
| 3747 | Cheryl Suarez | 2 | 1 | 14 | 1 | 0.09 |
| 3748 | Jacek Gorol | 1 | 1 | 8 | 7 | 0.09 |
| 3749 | Tadeusz Majorek | 1 | 1 | 8 | 7 | 0.09 |
| 3750 | Geneviève Duhamel | 1 | 1 | 19 | 4 | 0.09 |
| 3751 | Johan Hermann | 1 | 1 | 19 | 4 | 0.09 |
| 3752 | Katie Hartman | 1 | 1 | 19 | 4 | 0.09 |
| 3753 | Magnus Geisler | 1 | 1 | 19 | 4 | 0.09 |
| 3754 | Matthew Good | 1 | 1 | 19 | 4 | 0.09 |
| 3755 | Michel Dippel | 1 | 1 | 19 | 4 | 0.09 |
| 3756 | Brigitte Gotthard | 2 | 1 | 10 | 2 | 0.08 |
| 3757 | Yong Yang | 2 | 1 | 10 | 2 | 0.08 |
| 3758 | Bryan Davis | 1 | 1 | 15 | 5 | 0.08 |
| 3759 | Gina Cox | 1 | 1 | 15 | 5 | 0.08 |
| 3760 | Sherry Martin | 1 | 1 | 15 | 5 | 0.08 |
| 3761 | Rigo Becker | 2 | 2 | 0 | 0 | 0.08 |
| 3762 | Curtis Underwood | 1 | 1 | 22 | 3 | 0.08 |
| 3763 | Franklin Allen | 1 | 1 | 22 | 3 | 0.08 |
| 3764 | Jolanta Zirme | 1 | 1 | 22 | 3 | 0.08 |
| 3765 | Siegmund Winkler | 1 | 1 | 22 | 3 | 0.08 |
| 3766 | Wendy Porter | 1 | 1 | 22 | 3 | 0.08 |
| 3767 | Brandon Wilson | 2 | 1 | 13 | 1 | 0.08 |
| 3768 | Jeanne Miller | 2 | 1 | 13 | 1 | 0.08 |
| 3769 | Wei Zhong | 2 | 1 | 13 | 1 | 0.08 |
| 3770 | Sandra Majak | 1 | 1 | 7 | 7 | 0.08 |
| 3771 | Alexandra Obrien | 1 | 1 | 18 | 4 | 0.08 |
| 3772 | Carmine Harloff | 1 | 1 | 18 | 4 | 0.08 |
| 3773 | Cynthia Reed | 1 | 1 | 18 | 4 | 0.08 |
| 3774 | Ida Stolze-Lübs | 1 | 1 | 18 | 4 | 0.08 |
| 3775 | Juan Zhao | 1 | 1 | 18 | 4 | 0.08 |
| 3776 | Kerry Henry | 1 | 1 | 18 | 4 | 0.08 |
| 3777 | Marcus Berry | 1 | 1 | 18 | 4 | 0.08 |
| 3778 | Michele Sharp | 1 | 1 | 18 | 4 | 0.08 |
| 3779 | Gang Xiong | 2 | 1 | 9 | 2 | 0.08 |
| 3780 | Karina Gunpf | 2 | 1 | 9 | 2 | 0.08 |
| 3781 | Jun Hou | 1 | 1 | 14 | 5 | 0.08 |
| 3782 | Steven Ray | 1 | 1 | 14 | 5 | 0.08 |
| 3783 | Jessica Lindsey | 1 | 1 | 25 | 2 | 0.08 |
| 3784 | Chao Su | 1 | 1 | 21 | 3 | 0.08 |
| 3785 | Christopher Leonard | 1 | 1 | 21 | 3 | 0.08 |
| 3786 | Ethan Sanchez | 1 | 1 | 21 | 3 | 0.08 |
| 3787 | Tao Hao | 1 | 1 | 21 | 3 | 0.08 |
| 3788 | Jun Lai | 2 | 1 | 12 | 1 | 0.08 |
| 3789 | Arthur Sparks | 1 | 1 | 17 | 4 | 0.08 |
| 3790 | Betti Löffler | 1 | 1 | 17 | 4 | 0.08 |
| 3791 | Florence Martin | 1 | 1 | 17 | 4 | 0.08 |
| 3792 | Ida Loos | 1 | 1 | 17 | 4 | 0.08 |
| 3793 | Krystal Martin | 1 | 1 | 17 | 4 | 0.08 |
| 3794 | Laura Hernandez | 1 | 0 | 23 | 7 | 0.08 |
| 3795 | Zachary Stanley | 1 | 0 | 23 | 7 | 0.08 |
| 3796 | Collective Conscience | 2 | 1 | 8 | 2 | 0.08 |
| 3797 | Melissa Smith | 2 | 1 | 15 | 0 | 0.08 |
| 3798 | Anna Gonzales | 1 | 1 | 20 | 3 | 0.08 |
| 3799 | Gerhild Schweitzer | 1 | 1 | 20 | 3 | 0.08 |
| 3800 | Hasso Kreusel | 1 | 1 | 20 | 3 | 0.08 |
| 3801 | Jasmine Moore | 1 | 1 | 20 | 3 | 0.08 |
| 3802 | Joy Wood | 1 | 1 | 20 | 3 | 0.08 |
| 3803 | Mathilde Hesse | 1 | 1 | 20 | 3 | 0.08 |
| 3804 | Qiang Liao | 1 | 1 | 20 | 3 | 0.08 |
| 3805 | Tina Watson | 1 | 1 | 20 | 3 | 0.08 |
| 3806 | Yan Zheng | 1 | 1 | 20 | 3 | 0.08 |
| 3807 | Bas Jansen | 1 | 1 | 16 | 4 | 0.08 |
| 3808 | Hailey Timmerman-van der Berg | 1 | 1 | 16 | 4 | 0.08 |
| 3809 | Lily Sprong | 1 | 1 | 16 | 4 | 0.08 |
| 3810 | Sherri Mclaughlin | 1 | 1 | 12 | 5 | 0.08 |
| 3811 | Kendra Walsh | 1 | 1 | 23 | 2 | 0.08 |
| 3812 | Kyle Reynolds | 1 | 1 | 23 | 2 | 0.08 |
| 3813 | Nicholas Patel | 1 | 1 | 23 | 2 | 0.08 |
| 3814 | Alan Mcgee | 1 | 1 | 19 | 3 | 0.08 |
| 3815 | Amanda Hunter | 1 | 1 | 19 | 3 | 0.08 |
| 3816 | Antonio Fuentes | 1 | 1 | 19 | 3 | 0.08 |
| 3817 | Arnaude Poirier | 1 | 1 | 19 | 3 | 0.08 |
| 3818 | Brenda Anderson | 1 | 1 | 19 | 3 | 0.08 |
| 3819 | Cheryl Martinez | 1 | 1 | 19 | 3 | 0.08 |
| 3820 | Christophe-Émile Grégoire | 1 | 1 | 19 | 3 | 0.08 |
| 3821 | Georges Chrétien | 1 | 1 | 19 | 3 | 0.08 |
| 3822 | Jaime Watkins | 1 | 1 | 19 | 3 | 0.08 |
| 3823 | Jonathan Avila | 1 | 1 | 19 | 3 | 0.08 |
| 3824 | Lisa Shaw | 1 | 1 | 19 | 3 | 0.08 |
| 3825 | Lori Williams | 1 | 1 | 19 | 3 | 0.08 |
| 3826 | Luce Loiseau | 1 | 1 | 19 | 3 | 0.08 |
| 3827 | Mark Barr | 1 | 1 | 19 | 3 | 0.08 |
| 3828 | Mark Thomas | 1 | 1 | 19 | 3 | 0.08 |
| 3829 | Min Gong | 1 | 1 | 19 | 3 | 0.08 |
| 3830 | Nicolas Gosselin du Robert | 1 | 1 | 19 | 3 | 0.08 |
| 3831 | Tracy Bennett | 1 | 1 | 19 | 3 | 0.08 |
| 3832 | William Carter | 1 | 1 | 19 | 3 | 0.08 |
| 3833 | Jing Huang | 2 | 1 | 10 | 1 | 0.08 |
| 3834 | Yan Sun | 2 | 1 | 10 | 1 | 0.08 |
| 3835 | Alan Clark | 1 | 1 | 15 | 4 | 0.08 |
| 3836 | Andrew Martin | 1 | 1 | 15 | 4 | 0.08 |
| 3837 | Emily Drake | 1 | 1 | 15 | 4 | 0.08 |
| 3838 | Tamara Miller | 1 | 1 | 15 | 4 | 0.08 |
| 3839 | Greca Matteotti-Jovinelli | 1 | 1 | 11 | 5 | 0.08 |
| 3840 | Michelotto Toldo | 1 | 1 | 11 | 5 | 0.08 |
| 3841 | April Anderson | 1 | 1 | 22 | 2 | 0.08 |
| 3842 | Dana Walters | 1 | 1 | 22 | 2 | 0.08 |
| 3843 | Daniel Edwards | 1 | 1 | 22 | 2 | 0.08 |
| 3844 | Deborah Brown | 1 | 1 | 22 | 2 | 0.08 |
| 3845 | Derek Cook | 1 | 1 | 22 | 2 | 0.08 |
| 3846 | Elizabeth West | 1 | 1 | 22 | 2 | 0.08 |
| 3847 | Jared Arnold | 1 | 1 | 22 | 2 | 0.08 |
| 3848 | Jeremy Macias | 1 | 1 | 22 | 2 | 0.08 |
| 3849 | Jonathan Garcia | 1 | 1 | 22 | 2 | 0.08 |
| 3850 | Ralph Johnston | 1 | 1 | 22 | 2 | 0.08 |
| 3851 | Stacy Bryant | 1 | 1 | 22 | 2 | 0.08 |
| 3852 | Tanya Evans | 1 | 1 | 22 | 2 | 0.08 |
| 3853 | Todd Jones | 1 | 1 | 22 | 2 | 0.08 |
| 3854 | Victoria Butler | 1 | 1 | 22 | 2 | 0.08 |
| 3855 | Darlene Watson | 1 | 1 | 18 | 3 | 0.08 |
| 3856 | Darryl Curtis | 1 | 1 | 18 | 3 | 0.08 |
| 3857 | Janette Schleich | 1 | 1 | 18 | 3 | 0.08 |
| 3858 | Joseph Reyes | 1 | 1 | 18 | 3 | 0.08 |
| 3859 | Kevin Pruitt | 1 | 1 | 18 | 3 | 0.08 |
| 3860 | Marcel Kreusel | 1 | 1 | 18 | 3 | 0.08 |
| 3861 | Maria Powell | 1 | 1 | 18 | 3 | 0.08 |
| 3862 | Mikayla Russell | 1 | 1 | 18 | 3 | 0.08 |
| 3863 | Ralf Budig | 1 | 1 | 18 | 3 | 0.08 |
| 3864 | Carrie Cobb | 1 | 1 | 14 | 4 | 0.08 |
| 3865 | Gilles Raymond | 1 | 1 | 14 | 4 | 0.08 |
| 3866 | Justin Sullivan | 1 | 1 | 14 | 4 | 0.08 |
| 3867 | Kathleen Carroll | 1 | 1 | 14 | 4 | 0.08 |
| 3868 | Kenneth Knight | 1 | 1 | 14 | 4 | 0.08 |
| 3869 | Tammy Higgins | 1 | 1 | 14 | 4 | 0.08 |
| 3870 | Tiffany Lutz | 1 | 1 | 14 | 4 | 0.08 |
| 3871 | Nathaniel Craig | 2 | 1 | 5 | 2 | 0.08 |
| 3872 | Denise Barthelemy de Brunet | 1 | 1 | 21 | 2 | 0.08 |
| 3873 | Dina Scholten | 1 | 1 | 21 | 2 | 0.08 |
| 3874 | Jamie Garcia | 1 | 1 | 21 | 2 | 0.08 |
| 3875 | Kornelia Michnik | 1 | 1 | 21 | 2 | 0.08 |
| 3876 | Kristopher Roberts | 1 | 1 | 21 | 2 | 0.08 |
| 3877 | Na Qiao | 1 | 1 | 21 | 2 | 0.08 |
| 3878 | Nathalie Beer-Huhn | 1 | 1 | 21 | 2 | 0.08 |
| 3879 | Nicola Strangio | 1 | 1 | 21 | 2 | 0.08 |
| 3880 | Nicole Murphy | 1 | 1 | 21 | 2 | 0.08 |
| 3881 | Roberto Govoni | 1 | 1 | 21 | 2 | 0.08 |
| 3882 | Sherry Salinas | 1 | 1 | 21 | 2 | 0.08 |
| 3883 | Stephanie Murray | 1 | 1 | 21 | 2 | 0.08 |
| 3884 | Annunziata Trezzini | 1 | 1 | 17 | 3 | 0.08 |
| 3885 | Donna Vecellio | 1 | 1 | 17 | 3 | 0.08 |
| 3886 | Fulvio Comisso | 1 | 1 | 17 | 3 | 0.08 |
| 3887 | Jim Miller | 1 | 1 | 17 | 3 | 0.08 |
| 3888 | Monica Thompson | 1 | 1 | 17 | 3 | 0.08 |
| 3889 | Ping Xiao | 1 | 1 | 17 | 3 | 0.08 |
| 3890 | Sophia Cilea | 1 | 1 | 17 | 3 | 0.08 |
| 3891 | Steven Goodman | 1 | 1 | 17 | 3 | 0.08 |
| 3892 | Alexandra Taylor | 1 | 1 | 13 | 4 | 0.08 |
| 3893 | Baudelio Naranjo Ríos | 1 | 1 | 13 | 4 | 0.08 |
| 3894 | Birger Gutknecht | 1 | 1 | 13 | 4 | 0.08 |
| 3895 | Cameron Cohen | 1 | 1 | 13 | 4 | 0.08 |
| 3896 | Charvi Bains | 1 | 1 | 13 | 4 | 0.08 |
| 3897 | Haley Campbell | 1 | 1 | 13 | 4 | 0.08 |
| 3898 | Heinz-Günter Schmiedecke | 1 | 1 | 13 | 4 | 0.08 |
| 3899 | Holm Segebahn | 1 | 1 | 13 | 4 | 0.08 |
| 3900 | Hrishita Sura | 1 | 1 | 13 | 4 | 0.08 |
| 3901 | Ibrahim Heerkens-Everde | 1 | 1 | 13 | 4 | 0.08 |
| 3902 | Klaus-Werner Gerlach | 1 | 1 | 13 | 4 | 0.08 |
| 3903 | Megan Bowers | 1 | 1 | 13 | 4 | 0.08 |
| 3904 | Paca Ema Mosquera Cepeda | 1 | 1 | 13 | 4 | 0.08 |
| 3905 | Plinio Ribas | 1 | 1 | 13 | 4 | 0.08 |
| 3906 | Robby Schmiedecke | 1 | 1 | 13 | 4 | 0.08 |
| 3907 | Rocío Rovira | 1 | 1 | 13 | 4 | 0.08 |
| 3908 | Ulises Gomila Morell | 1 | 1 | 13 | 4 | 0.08 |
| 3909 | Valerie Levine | 1 | 1 | 13 | 4 | 0.08 |
| 3910 | Xiuying Yang | 1 | 1 | 13 | 4 | 0.08 |
| 3911 | Astrid Jockel-Hecker | 1 | 1 | 24 | 1 | 0.07 |
| 3912 | Denis Pechel | 1 | 1 | 24 | 1 | 0.07 |
| 3913 | Eckehard Kabus-Barth | 1 | 1 | 24 | 1 | 0.07 |
| 3914 | Elias Beyer | 1 | 1 | 24 | 1 | 0.07 |
| 3915 | Erhard Blümel | 1 | 1 | 24 | 1 | 0.07 |
| 3916 | Ernst-August Hamann-Junck | 1 | 1 | 24 | 1 | 0.07 |
| 3917 | Franco Dietz | 1 | 1 | 24 | 1 | 0.07 |
| 3918 | Gerfried Schaaf | 1 | 1 | 24 | 1 | 0.07 |
| 3919 | Inna Wagner | 1 | 1 | 24 | 1 | 0.07 |
| 3920 | Irmtrud Jessel | 1 | 1 | 24 | 1 | 0.07 |
| 3921 | Isabelle Bloch | 1 | 1 | 24 | 1 | 0.07 |
| 3922 | Ivonne Austermühle | 1 | 1 | 24 | 1 | 0.07 |
| 3923 | Juan Brown | 1 | 1 | 24 | 1 | 0.07 |
| 3924 | Margarete Löchel | 1 | 1 | 24 | 1 | 0.07 |
| 3925 | Mirja Heintze | 1 | 1 | 24 | 1 | 0.07 |
| 3926 | Pawel Zirme | 1 | 1 | 24 | 1 | 0.07 |
| 3927 | Sarah Miles | 1 | 1 | 24 | 1 | 0.07 |
| 3928 | Sevim Holt | 1 | 1 | 24 | 1 | 0.07 |
| 3929 | Sieghard Jäntsch-Kensy | 1 | 1 | 24 | 1 | 0.07 |
| 3930 | Jo Baker | 1 | 1 | 9 | 5 | 0.07 |
| 3931 | Brandon Griffith | 1 | 1 | 20 | 2 | 0.07 |
| 3932 | Dominik Preiß | 1 | 1 | 20 | 2 | 0.07 |
| 3933 | Ping Liu | 1 | 1 | 20 | 2 | 0.07 |
| 3934 | Jun Liao | 2 | 1 | 11 | 0 | 0.07 |
| 3935 | Adira Chaudhuri | 1 | 1 | 5 | 6 | 0.07 |
| 3936 | Bart Wensen-Kof | 1 | 1 | 16 | 3 | 0.07 |
| 3937 | Danny Fitzgerald | 1 | 1 | 16 | 3 | 0.07 |
| 3938 | Eric Hopkins | 1 | 1 | 16 | 3 | 0.07 |
| 3939 | Kristina Sanchez | 1 | 1 | 16 | 3 | 0.07 |
| 3940 | Lieve van Riet | 1 | 1 | 16 | 3 | 0.07 |
| 3941 | Lizz van Santen | 1 | 1 | 16 | 3 | 0.07 |
| 3942 | Mary Jacobs | 1 | 1 | 16 | 3 | 0.07 |
| 3943 | Melissa Rush | 1 | 1 | 16 | 3 | 0.07 |
| 3944 | Min Yang | 1 | 1 | 16 | 3 | 0.07 |
| 3945 | Nina Mallien | 1 | 1 | 16 | 3 | 0.07 |
| 3946 | Ryan Mcguire | 1 | 1 | 16 | 3 | 0.07 |
| 3947 | Stephen Allen | 1 | 1 | 16 | 3 | 0.07 |
| 3948 | Tanya Ratta | 1 | 1 | 16 | 3 | 0.07 |
| 3949 | Ulf Kusch | 2 | 1 | 7 | 1 | 0.07 |
| 3950 | Gitta Wilmsen | 1 | 1 | 12 | 4 | 0.07 |
| 3951 | Larry Mendez | 1 | 1 | 12 | 4 | 0.07 |
| 3952 | Lisa Crawford | 2 | 1 | 3 | 2 | 0.07 |
| 3953 | Kimberly Dominguez | 1 | 1 | 8 | 5 | 0.07 |
| 3954 | Ricky Franklin | 1 | 1 | 8 | 5 | 0.07 |
| 3955 | Alexander Carr | 1 | 1 | 19 | 2 | 0.07 |
| 3956 | Amanda Peterson | 1 | 1 | 19 | 2 | 0.07 |
| 3957 | Baptist Gierschner | 1 | 1 | 19 | 2 | 0.07 |
| 3958 | Colleen Richards | 1 | 1 | 19 | 2 | 0.07 |
| 3959 | Elizabeth Bradshaw | 1 | 1 | 19 | 2 | 0.07 |
| 3960 | Joseph Ho | 1 | 1 | 19 | 2 | 0.07 |
| 3961 | Madeleine Wulf | 1 | 1 | 19 | 2 | 0.07 |
| 3962 | Rosalie Hörle | 1 | 1 | 19 | 2 | 0.07 |
| 3963 | Savannah Shaw | 1 | 1 | 19 | 2 | 0.07 |
| 3964 | Anthony Smith | 2 | 1 | 10 | 0 | 0.07 |
| 3965 | Guiying Qian | 2 | 1 | 10 | 0 | 0.07 |
| 3966 | Qiang Duan | 2 | 1 | 10 | 0 | 0.07 |
| 3967 | Jing Xu | 1 | 1 | 15 | 3 | 0.07 |
| 3968 | Kai-Uwe Döring | 1 | 1 | 15 | 3 | 0.07 |
| 3969 | Robert Allen | 1 | 1 | 15 | 3 | 0.07 |
| 3970 | Yoko Murakami | 1 | 1 | 15 | 3 | 0.07 |
| 3971 | Annunziata Bertoli-Ruberto | 2 | 1 | 6 | 1 | 0.07 |
| 3972 | Antoine du Adam | 2 | 1 | 6 | 1 | 0.07 |
| 3973 | Augustin Raymond | 2 | 1 | 6 | 1 | 0.07 |
| 3974 | Chantal Gérard | 2 | 1 | 6 | 1 | 0.07 |
| 3975 | Claudine Leleu | 2 | 1 | 6 | 1 | 0.07 |
| 3976 | Julien Collin-Texier | 2 | 1 | 6 | 1 | 0.07 |
| 3977 | Min Han | 2 | 1 | 6 | 1 | 0.07 |
| 3978 | Sylvie-Chantal Schmitt | 2 | 1 | 6 | 1 | 0.07 |
| 3979 | Eva Sani | 1 | 1 | 11 | 4 | 0.07 |
| 3980 | Lia Wähner-Weimer | 1 | 1 | 11 | 4 | 0.07 |
| 3981 | Stacy Hudson | 1 | 1 | 11 | 4 | 0.07 |
| 3982 | Steven Carter | 1 | 1 | 11 | 4 | 0.07 |
| 3983 | Feliciano Noguera-Vallejo | 2 | 1 | 2 | 2 | 0.07 |
| 3984 | Natasza Sygut | 1 | 1 | 7 | 5 | 0.07 |
| 3985 | Pamela Graham | 1 | 1 | 7 | 5 | 0.07 |
| 3986 | Aaron Conway | 1 | 1 | 18 | 2 | 0.07 |
| 3987 | Adam Hanna | 1 | 1 | 18 | 2 | 0.07 |
| 3988 | Alexandria Spencer | 1 | 1 | 18 | 2 | 0.07 |
| 3989 | Allison Johnson | 1 | 1 | 18 | 2 | 0.07 |
| 3990 | Amber Franklin | 1 | 1 | 18 | 2 | 0.07 |
| 3991 | Chris Meyer | 1 | 1 | 18 | 2 | 0.07 |
| 3992 | Fang Shao | 1 | 1 | 18 | 2 | 0.07 |
| 3993 | Jody Lopez | 1 | 1 | 18 | 2 | 0.07 |
| 3994 | Leslie Wagner | 1 | 1 | 18 | 2 | 0.07 |
| 3995 | Marie Flores | 1 | 1 | 18 | 2 | 0.07 |
| 3996 | Ming Peng | 1 | 1 | 18 | 2 | 0.07 |
| 3997 | Molly Williams | 1 | 1 | 18 | 2 | 0.07 |
| 3998 | Sabrina Mcmahon | 1 | 1 | 18 | 2 | 0.07 |
| 3999 | William Stone | 1 | 1 | 18 | 2 | 0.07 |
| 4000 | George Jones | 2 | 1 | 9 | 0 | 0.07 |
| 4001 | Ming Deng | 2 | 1 | 9 | 0 | 0.07 |
| 4002 | Nicole Smith | 2 | 1 | 9 | 0 | 0.07 |
| 4003 | Anaya Randhawa | 1 | 1 | 14 | 3 | 0.07 |
| 4004 | Anvi Chawla | 1 | 1 | 14 | 3 | 0.07 |
| 4005 | Steven Green | 1 | 1 | 14 | 3 | 0.07 |
| 4006 | Yuvaan Tripathi | 1 | 1 | 14 | 3 | 0.07 |
| 4007 | Carla Gross | 2 | 1 | 5 | 1 | 0.07 |
| 4008 | Craig Aguilar | 1 | 1 | 10 | 4 | 0.07 |
| 4009 | Jon Peters | 1 | 1 | 10 | 4 | 0.07 |
| 4010 | Jeffery Williams | 1 | 1 | 21 | 1 | 0.07 |
| 4011 | Šimon Urban | 1 | 1 | 21 | 1 | 0.07 |
| 4012 | Devansh Seshadri | 1 | 1 | 6 | 5 | 0.07 |
| 4013 | Alexander Whitney | 1 | 1 | 17 | 2 | 0.07 |
| 4014 | Angela Porter | 1 | 1 | 17 | 2 | 0.07 |
| 4015 | Edwin Binner | 1 | 1 | 17 | 2 | 0.07 |
| 4016 | Evelyn Gordon | 1 | 1 | 17 | 2 | 0.07 |
| 4017 | Gang Wang | 1 | 1 | 17 | 2 | 0.07 |
| 4018 | Gernot Karz | 1 | 1 | 17 | 2 | 0.07 |
| 4019 | Gregory White | 1 | 1 | 17 | 2 | 0.07 |
| 4020 | Hansjoachim Sager | 1 | 1 | 17 | 2 | 0.07 |
| 4021 | Ian Jüttner | 1 | 1 | 17 | 2 | 0.07 |
| 4022 | James Maldonado | 1 | 1 | 17 | 2 | 0.07 |
| 4023 | Joseph Parsons | 1 | 1 | 17 | 2 | 0.07 |
| 4024 | Joshua Anderson | 1 | 1 | 17 | 2 | 0.07 |
| 4025 | Lori Gregory | 1 | 1 | 17 | 2 | 0.07 |
| 4026 | Mary Cisneros | 1 | 1 | 17 | 2 | 0.07 |
| 4027 | Matthew Fields | 1 | 1 | 17 | 2 | 0.07 |
| 4028 | Richard Frazier | 1 | 1 | 17 | 2 | 0.07 |
| 4029 | Rodney Clark | 1 | 1 | 17 | 2 | 0.07 |
| 4030 | Sonia Weeks | 1 | 1 | 17 | 2 | 0.07 |
| 4031 | Vanessa Clark | 1 | 1 | 17 | 2 | 0.07 |
| 4032 | Yang Shao | 2 | 1 | 8 | 0 | 0.07 |
| 4033 | Anaïs Peron | 1 | 1 | 13 | 3 | 0.07 |
| 4034 | Caleb Williamson | 1 | 1 | 13 | 3 | 0.07 |
| 4035 | Chad Green | 1 | 1 | 13 | 3 | 0.07 |
| 4036 | Diana Lledó Colomer | 1 | 1 | 13 | 3 | 0.07 |
| 4037 | Donald Bradley | 1 | 1 | 13 | 3 | 0.07 |
| 4038 | Jaime Arrieta | 1 | 1 | 13 | 3 | 0.07 |
| 4039 | Justin Wyatt | 1 | 1 | 13 | 3 | 0.07 |
| 4040 | Katie Johnston | 1 | 1 | 13 | 3 | 0.07 |
| 4041 | Livio Brenna | 1 | 1 | 13 | 3 | 0.07 |
| 4042 | Mai Yamada | 1 | 1 | 13 | 3 | 0.07 |
| 4043 | Margaret Woods | 1 | 1 | 13 | 3 | 0.07 |
| 4044 | Nino Pasolini | 1 | 1 | 13 | 3 | 0.07 |
| 4045 | Claire Garner | 2 | 1 | 4 | 1 | 0.07 |
| 4046 | Lauren Thomas | 2 | 1 | 4 | 1 | 0.07 |
| 4047 | Sheryl Massey | 2 | 1 | 4 | 1 | 0.07 |
| 4048 | Jacob Hunter | 1 | 1 | 9 | 4 | 0.07 |
| 4049 | Arkadiusz Ciesielka | 1 | 1 | 5 | 5 | 0.07 |
| 4050 | Adrien Boulay | 1 | 1 | 16 | 2 | 0.07 |
| 4051 | Alphonse-Jacques Ledoux | 1 | 1 | 16 | 2 | 0.07 |
| 4052 | Andre Scott | 1 | 1 | 16 | 2 | 0.07 |
| 4053 | Anna Mendez | 1 | 1 | 16 | 2 | 0.07 |
| 4054 | Annette Mckee | 1 | 1 | 16 | 2 | 0.07 |
| 4055 | April Morris | 1 | 1 | 16 | 2 | 0.07 |
| 4056 | Arthur Ollivier | 1 | 1 | 16 | 2 | 0.07 |
| 4057 | Athanasios Hamann | 1 | 1 | 16 | 2 | 0.07 |
| 4058 | Brianna Wilson | 1 | 1 | 16 | 2 | 0.07 |
| 4059 | Christopher Harris | 1 | 1 | 16 | 2 | 0.07 |
| 4060 | Eric Bartlett | 1 | 1 | 16 | 2 | 0.07 |
| 4061 | Gabriel Ferreira-Gillet | 1 | 1 | 16 | 2 | 0.07 |
| 4062 | James Harrington | 1 | 1 | 16 | 2 | 0.07 |
| 4063 | John Barnes | 1 | 1 | 16 | 2 | 0.07 |
| 4064 | Kelly Cummings | 1 | 1 | 16 | 2 | 0.07 |
| 4065 | Leah Farrell | 1 | 1 | 16 | 2 | 0.07 |
| 4066 | Lori Bass | 1 | 1 | 16 | 2 | 0.07 |
| 4067 | Lucie Prévost du Rousset | 1 | 1 | 16 | 2 | 0.07 |
| 4068 | Michael Carroll | 1 | 1 | 16 | 2 | 0.07 |
| 4069 | Michelle Garrett | 1 | 1 | 16 | 2 | 0.07 |
| 4070 | Milo Badoer | 1 | 1 | 16 | 2 | 0.07 |
| 4071 | Misty Reed | 1 | 1 | 16 | 2 | 0.07 |
| 4072 | Mitchell Hernandez | 1 | 1 | 16 | 2 | 0.07 |
| 4073 | Monica Hale | 1 | 1 | 16 | 2 | 0.07 |
| 4074 | Robert Adams | 1 | 1 | 16 | 2 | 0.07 |
| 4075 | Roderich Mohaupt | 1 | 1 | 16 | 2 | 0.07 |
| 4076 | Sara Shannon | 1 | 1 | 16 | 2 | 0.07 |
| 4077 | Steve Yu | 1 | 1 | 16 | 2 | 0.07 |
| 4078 | Susan Oneal | 1 | 1 | 16 | 2 | 0.07 |
| 4079 | Teresa White | 1 | 1 | 16 | 2 | 0.07 |
| 4080 | Thomas Beard | 1 | 1 | 16 | 2 | 0.07 |
| 4081 | Tiffany Lee | 1 | 1 | 16 | 2 | 0.07 |
| 4082 | Tonya Gallegos | 1 | 1 | 16 | 2 | 0.07 |
| 4083 | Jie Hao | 2 | 1 | 7 | 0 | 0.07 |
| 4084 | Kenneth Jones | 2 | 1 | 7 | 0 | 0.07 |
| 4085 | Kanav Sachar | 1 | 1 | 12 | 3 | 0.07 |
| 4086 | Melinda Austin | 1 | 1 | 12 | 3 | 0.07 |
| 4087 | Nayantara Bhatti | 1 | 1 | 12 | 3 | 0.07 |
| 4088 | Shray Kala | 1 | 1 | 12 | 3 | 0.07 |
| 4089 | Chad Garcia | 2 | 1 | 3 | 1 | 0.07 |
| 4090 | Donato Mocenigo | 2 | 1 | 3 | 1 | 0.07 |
| 4091 | Michael Snow | 2 | 0 | 20 | 1 | 0.07 |
| 4092 | Klara Kuźnia | 1 | 1 | 8 | 4 | 0.07 |
| 4093 | Arthur Miller | 1 | 1 | 19 | 1 | 0.07 |
| 4094 | Joshua Thomas | 1 | 1 | 19 | 1 | 0.07 |
| 4095 | Kathleen Bean | 1 | 1 | 19 | 1 | 0.07 |
| 4096 | Luis King | 1 | 1 | 19 | 1 | 0.07 |
| 4097 | Peggy West | 1 | 1 | 19 | 1 | 0.07 |
| 4098 | Sydney Gonzalez | 1 | 1 | 19 | 1 | 0.07 |
| 4099 | Felix Hornich | 2 | 0 | 16 | 2 | 0.07 |
| 4100 | Alex Ramsey | 1 | 1 | 15 | 2 | 0.07 |
| 4101 | Angela Kelly | 1 | 1 | 15 | 2 | 0.07 |
| 4102 | Ashley Larson | 1 | 1 | 15 | 2 | 0.07 |
| 4103 | Ashley Murphy | 1 | 1 | 15 | 2 | 0.07 |
| 4104 | Beatrix Schmidt | 1 | 1 | 15 | 2 | 0.07 |
| 4105 | Beth Thompson | 1 | 1 | 15 | 2 | 0.07 |
| 4106 | Bjorn van Berkum-Freshour | 1 | 1 | 15 | 2 | 0.07 |
| 4107 | Brian Moore | 1 | 1 | 15 | 2 | 0.07 |
| 4108 | Carmina Esteve Coloma | 1 | 1 | 15 | 2 | 0.07 |
| 4109 | Christina Garrett | 1 | 1 | 15 | 2 | 0.07 |
| 4110 | Daan VI-Cadefau | 1 | 1 | 15 | 2 | 0.07 |
| 4111 | Fang Yang | 1 | 1 | 15 | 2 | 0.07 |
| 4112 | Gary Chapman | 1 | 1 | 15 | 2 | 0.07 |
| 4113 | Hans-Karl Hövel | 1 | 1 | 15 | 2 | 0.07 |
| 4114 | Isabelle Rijn-Höning | 1 | 1 | 15 | 2 | 0.07 |
| 4115 | Jake Marchal | 1 | 1 | 15 | 2 | 0.07 |
| 4116 | Jeffrey Tate | 1 | 1 | 15 | 2 | 0.07 |
| 4117 | John Gallagher | 1 | 1 | 15 | 2 | 0.07 |
| 4118 | John Price | 1 | 1 | 15 | 2 | 0.07 |
| 4119 | Joshua Crawford | 1 | 1 | 15 | 2 | 0.07 |
| 4120 | Kathleen Martinez | 1 | 1 | 15 | 2 | 0.07 |
| 4121 | Kenneth West | 1 | 1 | 15 | 2 | 0.07 |
| 4122 | Larry Thomas | 1 | 1 | 15 | 2 | 0.07 |
| 4123 | Laura Guerrero Cañete | 1 | 1 | 15 | 2 | 0.07 |
| 4124 | Laura Lindsey | 1 | 1 | 15 | 2 | 0.07 |
| 4125 | Marina Stiebitz | 1 | 1 | 15 | 2 | 0.07 |
| 4126 | Melinda Vasquez | 1 | 1 | 15 | 2 | 0.07 |
| 4127 | Michael Kelly | 1 | 1 | 15 | 2 | 0.07 |
| 4128 | Nancy Gonzalez | 1 | 1 | 15 | 2 | 0.07 |
| 4129 | Olaf Schmiedt | 1 | 1 | 15 | 2 | 0.07 |
| 4130 | Pim de Roo | 1 | 1 | 15 | 2 | 0.07 |
| 4131 | Priska Hölzenbecher | 1 | 1 | 15 | 2 | 0.07 |
| 4132 | Qiang Ma | 1 | 1 | 15 | 2 | 0.07 |
| 4133 | Rania Banik | 1 | 1 | 15 | 2 | 0.07 |
| 4134 | Riya Ahluwalia | 1 | 1 | 15 | 2 | 0.07 |
| 4135 | Robert Rodriguez | 1 | 1 | 15 | 2 | 0.07 |
| 4136 | Ryan Reynolds | 1 | 1 | 15 | 2 | 0.07 |
| 4137 | Sarah Lee | 1 | 1 | 15 | 2 | 0.07 |
| 4138 | Sarah Young | 1 | 1 | 15 | 2 | 0.07 |
| 4139 | Stephen Ross | 1 | 1 | 15 | 2 | 0.07 |
| 4140 | Valerie Phillips | 1 | 1 | 15 | 2 | 0.07 |
| 4141 | Wayne Perkins | 1 | 1 | 15 | 2 | 0.07 |
| 4142 | William Duncan | 1 | 1 | 15 | 2 | 0.07 |
| 4143 | Yasuhiro Sato | 1 | 1 | 15 | 2 | 0.07 |
| 4144 | Borderlands | 2 | 1 | 6 | 0 | 0.07 |
| 4145 | Yong Ye | 2 | 1 | 6 | 0 | 0.07 |
| 4146 | Armaan Bera | 1 | 1 | 11 | 3 | 0.07 |
| 4147 | Benjamin Griffin | 1 | 1 | 11 | 3 | 0.07 |
| 4148 | Henry Scott | 1 | 1 | 11 | 3 | 0.07 |
| 4149 | Herr Ilhan Mülichen | 1 | 1 | 11 | 3 | 0.07 |
| 4150 | Gustaw Reich | 1 | 1 | 7 | 4 | 0.06 |
| 4151 | Jerzy Bochnak | 1 | 1 | 7 | 4 | 0.06 |
| 4152 | Leon Misiurek | 1 | 1 | 7 | 4 | 0.06 |
| 4153 | Marianna Polasik | 1 | 1 | 7 | 4 | 0.06 |
| 4154 | John Schmitt | 1 | 1 | 18 | 1 | 0.06 |
| 4155 | Kevin Parker | 1 | 1 | 18 | 1 | 0.06 |
| 4156 | Adam Christian | 1 | 1 | 14 | 2 | 0.06 |
| 4157 | Caitlin Miller | 1 | 1 | 14 | 2 | 0.06 |
| 4158 | Catherine Brooks | 1 | 1 | 14 | 2 | 0.06 |
| 4159 | Christopher Robbins | 1 | 1 | 14 | 2 | 0.06 |
| 4160 | Gang Liang | 1 | 1 | 14 | 2 | 0.06 |
| 4161 | Herbert Mcfarland | 1 | 1 | 14 | 2 | 0.06 |
| 4162 | Joseph Ponce | 1 | 1 | 14 | 2 | 0.06 |
| 4163 | Kevin King | 1 | 1 | 14 | 2 | 0.06 |
| 4164 | Laura Mejia | 1 | 1 | 14 | 2 | 0.06 |
| 4165 | Matthew Lara | 1 | 1 | 14 | 2 | 0.06 |
| 4166 | Megan Harris | 1 | 1 | 14 | 2 | 0.06 |
| 4167 | Ming Liao | 1 | 1 | 14 | 2 | 0.06 |
| 4168 | Nicholas Harris | 1 | 1 | 14 | 2 | 0.06 |
| 4169 | Rachel Montes | 1 | 1 | 14 | 2 | 0.06 |
| 4170 | Rebecca Wise | 1 | 1 | 14 | 2 | 0.06 |
| 4171 | Rosalinde Tintzmann | 1 | 1 | 14 | 2 | 0.06 |
| 4172 | Sean James | 1 | 1 | 14 | 2 | 0.06 |
| 4173 | Sebastian Vega Saldaña | 1 | 1 | 14 | 2 | 0.06 |
| 4174 | Stacey Martin | 1 | 1 | 14 | 2 | 0.06 |
| 4175 | Xiuying Qiao | 1 | 1 | 14 | 2 | 0.06 |
| 4176 | Yong Qin | 1 | 1 | 14 | 2 | 0.06 |
| 4177 | Elizabeth Gonzalez | 2 | 1 | 5 | 0 | 0.06 |
| 4178 | Katelyn Flores | 2 | 1 | 5 | 0 | 0.06 |
| 4179 | Nicole Miller | 2 | 1 | 5 | 0 | 0.06 |
| 4180 | Aradhya Dara | 1 | 1 | 10 | 3 | 0.06 |
| 4181 | Armaan Dalal | 1 | 1 | 10 | 3 | 0.06 |
| 4182 | Brian Mclaughlin | 1 | 1 | 10 | 3 | 0.06 |
| 4183 | Devin Berger | 1 | 1 | 10 | 3 | 0.06 |
| 4184 | Drishya Srinivasan | 1 | 1 | 10 | 3 | 0.06 |
| 4185 | Garrett Montoya | 1 | 1 | 10 | 3 | 0.06 |
| 4186 | Henry Gross | 1 | 1 | 10 | 3 | 0.06 |
| 4187 | Joanna Avery | 1 | 1 | 10 | 3 | 0.06 |
| 4188 | John Rodriguez | 1 | 1 | 10 | 3 | 0.06 |
| 4189 | Judy Yang | 1 | 1 | 10 | 3 | 0.06 |
| 4190 | Marcus Stewart | 1 | 1 | 10 | 3 | 0.06 |
| 4191 | Miss Jennifer Williams | 1 | 1 | 10 | 3 | 0.06 |
| 4192 | Molly Gonzalez | 1 | 1 | 10 | 3 | 0.06 |
| 4193 | William Robinson | 1 | 1 | 10 | 3 | 0.06 |
| 4194 | Jonathan Guerrero | 2 | 1 | 1 | 1 | 0.06 |
| 4195 | Autumn Johnson | 1 | 1 | 17 | 1 | 0.06 |
| 4196 | Craig Campbell | 1 | 1 | 17 | 1 | 0.06 |
| 4197 | Lauren Rich | 1 | 1 | 17 | 1 | 0.06 |
| 4198 | Li Peng | 1 | 1 | 17 | 1 | 0.06 |
| 4199 | Ramona Mezzetta | 1 | 1 | 17 | 1 | 0.06 |
| 4200 | Sydney James | 1 | 1 | 17 | 1 | 0.06 |
| 4201 | Alexis Dixon | 1 | 1 | 13 | 2 | 0.06 |
| 4202 | Alicia Koch | 1 | 1 | 13 | 2 | 0.06 |
| 4203 | Alina Leblanc | 1 | 1 | 13 | 2 | 0.06 |
| 4204 | Ana Sager | 1 | 1 | 13 | 2 | 0.06 |
| 4205 | Andrea Meyer | 1 | 1 | 13 | 2 | 0.06 |
| 4206 | Ann Schmidt | 1 | 1 | 13 | 2 | 0.06 |
| 4207 | Anthony Scott | 1 | 1 | 13 | 2 | 0.06 |
| 4208 | Audrey Gray | 1 | 1 | 13 | 2 | 0.06 |
| 4209 | Austin Perez | 1 | 1 | 13 | 2 | 0.06 |
| 4210 | Chad Gonzales | 1 | 1 | 13 | 2 | 0.06 |
| 4211 | Chao Gu | 1 | 1 | 13 | 2 | 0.06 |
| 4212 | Christoph Hermann | 1 | 1 | 13 | 2 | 0.06 |
| 4213 | Christopher Hughes | 1 | 1 | 13 | 2 | 0.06 |
| 4214 | Constance Meyer | 1 | 1 | 13 | 2 | 0.06 |
| 4215 | David Nash | 1 | 1 | 13 | 2 | 0.06 |
| 4216 | Debra Curry | 1 | 1 | 13 | 2 | 0.06 |
| 4217 | Denise Poole | 1 | 1 | 13 | 2 | 0.06 |
| 4218 | Diane Robbins | 1 | 1 | 13 | 2 | 0.06 |
| 4219 | Fang Liao | 1 | 1 | 13 | 2 | 0.06 |
| 4220 | Fatma Henck-Weinhold | 1 | 1 | 13 | 2 | 0.06 |
| 4221 | Godofredo Franch Sanabria | 1 | 1 | 13 | 2 | 0.06 |
| 4222 | Herr Henry Grein Groth | 1 | 1 | 13 | 2 | 0.06 |
| 4223 | James Murray | 1 | 1 | 13 | 2 | 0.06 |
| 4224 | Jessica Beck | 1 | 1 | 13 | 2 | 0.06 |
| 4225 | Jose Harmon | 1 | 1 | 13 | 2 | 0.06 |
| 4226 | Kaori Kobayashi | 1 | 1 | 13 | 2 | 0.06 |
| 4227 | Kenneth Miller | 1 | 1 | 13 | 2 | 0.06 |
| 4228 | Lei Mao | 1 | 1 | 13 | 2 | 0.06 |
| 4229 | Lindsey Terry | 1 | 1 | 13 | 2 | 0.06 |
| 4230 | Lisa Ramos | 1 | 1 | 13 | 2 | 0.06 |
| 4231 | Lucas Hurley | 1 | 1 | 13 | 2 | 0.06 |
| 4232 | Luigina Lattuada-Carfagna | 1 | 1 | 13 | 2 | 0.06 |
| 4233 | Marilyn Austin | 1 | 1 | 13 | 2 | 0.06 |
| 4234 | Marina Giradello-Pellegrini | 1 | 1 | 13 | 2 | 0.06 |
| 4235 | Matilda Gottardi | 1 | 1 | 13 | 2 | 0.06 |
| 4236 | Raffaele Cantimori-Nicolini | 1 | 1 | 13 | 2 | 0.06 |
| 4237 | Raymond de la Lebrun | 1 | 1 | 13 | 2 | 0.06 |
| 4238 | Roswita Weinhold | 1 | 1 | 13 | 2 | 0.06 |
| 4239 | Stefani Magrassi | 1 | 1 | 13 | 2 | 0.06 |
| 4240 | Tiziano Bianchi | 1 | 1 | 13 | 2 | 0.06 |
| 4241 | Vincenza Tropea | 1 | 1 | 13 | 2 | 0.06 |
| 4242 | Wei Lai | 1 | 1 | 13 | 2 | 0.06 |
| 4243 | Xia Liu | 1 | 1 | 13 | 2 | 0.06 |
| 4244 | Yui Kondo | 1 | 1 | 13 | 2 | 0.06 |
| 4245 | Zachary Estes | 1 | 1 | 13 | 2 | 0.06 |
| 4246 | Zachary Woods | 1 | 1 | 13 | 2 | 0.06 |
| 4247 | Aria Stone | 2 | 1 | 4 | 0 | 0.06 |
| 4248 | Ash Mercer | 2 | 1 | 4 | 0 | 0.06 |
| 4249 | Audrey Huff | 2 | 1 | 4 | 0 | 0.06 |
| 4250 | Green Haze Collective | 2 | 1 | 4 | 0 | 0.06 |
| 4251 | Jax Holloway | 2 | 1 | 4 | 0 | 0.06 |
| 4252 | Jaxon Rivers | 2 | 1 | 4 | 0 | 0.06 |
| 4253 | Lila Green | 2 | 1 | 4 | 0 | 0.06 |
| 4254 | Riley Vex | 2 | 1 | 4 | 0 | 0.06 |
| 4255 | Theo Gray | 2 | 1 | 4 | 0 | 0.06 |
| 4256 | Bartek Krzysiek | 1 | 1 | 9 | 3 | 0.06 |
| 4257 | Charles Brown | 1 | 1 | 9 | 3 | 0.06 |
| 4258 | Franck Gillet | 1 | 1 | 9 | 3 | 0.06 |
| 4259 | Gertrude Dietz-Drub | 1 | 1 | 9 | 3 | 0.06 |
| 4260 | Gokul Konda | 1 | 1 | 9 | 3 | 0.06 |
| 4261 | Hanna Aelftrud van Wessex | 1 | 1 | 9 | 3 | 0.06 |
| 4262 | Imran de Bruijn-Hendrikse | 1 | 1 | 9 | 3 | 0.06 |
| 4263 | Krista Fritsch | 1 | 1 | 9 | 3 | 0.06 |
| 4264 | Michael Hart | 1 | 1 | 9 | 3 | 0.06 |
| 4265 | Michelle Moore | 1 | 1 | 9 | 3 | 0.06 |
| 4266 | Prerak Keer | 1 | 1 | 9 | 3 | 0.06 |
| 4267 | Rocco Hauffer | 1 | 1 | 9 | 3 | 0.06 |
| 4268 | Thilo Sölzer | 1 | 1 | 9 | 3 | 0.06 |
| 4269 | Xiulan Xiong | 1 | 1 | 9 | 3 | 0.06 |
| 4270 | Kimberly Weaver | 1 | 1 | 5 | 4 | 0.06 |
| 4271 | Alan Mcclain | 1 | 1 | 16 | 1 | 0.06 |
| 4272 | Andrew Medina | 1 | 1 | 16 | 1 | 0.06 |
| 4273 | Ashley Williams | 1 | 1 | 16 | 1 | 0.06 |
| 4274 | Brianna Logan | 1 | 1 | 16 | 1 | 0.06 |
| 4275 | Brianna Tucker | 1 | 1 | 16 | 1 | 0.06 |
| 4276 | Christina Berry | 1 | 1 | 16 | 1 | 0.06 |
| 4277 | Debra Bates | 1 | 1 | 16 | 1 | 0.06 |
| 4278 | Franca Wilms | 1 | 1 | 16 | 1 | 0.06 |
| 4279 | Haley Walls | 1 | 1 | 16 | 1 | 0.06 |
| 4280 | Jake Casey | 1 | 1 | 16 | 1 | 0.06 |
| 4281 | Jeffery Koch | 1 | 1 | 16 | 1 | 0.06 |
| 4282 | Joseph Crawford | 1 | 1 | 16 | 1 | 0.06 |
| 4283 | Justin Mcclain | 1 | 1 | 16 | 1 | 0.06 |
| 4284 | Kelly Sweeney | 1 | 1 | 16 | 1 | 0.06 |
| 4285 | Matthew Hickman | 1 | 1 | 16 | 1 | 0.06 |
| 4286 | Melanie Barker | 1 | 1 | 16 | 1 | 0.06 |
| 4287 | Nicole Gray | 1 | 1 | 16 | 1 | 0.06 |
| 4288 | Rebecca Mcneil | 1 | 1 | 16 | 1 | 0.06 |
| 4289 | Richard Richards | 1 | 1 | 16 | 1 | 0.06 |
| 4290 | Rodney Hurst | 1 | 1 | 16 | 1 | 0.06 |
| 4291 | Zachary Stark | 1 | 1 | 16 | 1 | 0.06 |
| 4292 | Adrienne Bouchet | 1 | 1 | 12 | 2 | 0.06 |
| 4293 | Akira Saito | 1 | 1 | 12 | 2 | 0.06 |
| 4294 | Alex Moore | 1 | 1 | 12 | 2 | 0.06 |
| 4295 | Alfons Rudolph-Holzapfel | 1 | 1 | 12 | 2 | 0.06 |
| 4296 | Amanda Brown | 1 | 1 | 12 | 2 | 0.06 |
| 4297 | Amanda Sullivan | 1 | 1 | 12 | 2 | 0.06 |
| 4298 | Anthony Allen | 1 | 1 | 12 | 2 | 0.06 |
| 4299 | Brandon Kirby | 1 | 1 | 12 | 2 | 0.06 |
| 4300 | Brian Carter | 1 | 1 | 12 | 2 | 0.06 |
| 4301 | Brittany Moreno | 1 | 1 | 12 | 2 | 0.06 |
| 4302 | Caroline Navarro | 1 | 1 | 12 | 2 | 0.06 |
| 4303 | Christine Martin | 1 | 1 | 12 | 2 | 0.06 |
| 4304 | Clemens Henck | 1 | 1 | 12 | 2 | 0.06 |
| 4305 | Cécile Meyer | 1 | 1 | 12 | 2 | 0.06 |
| 4306 | Diether Lachmann | 1 | 1 | 12 | 2 | 0.06 |
| 4307 | Edward Clark | 1 | 1 | 12 | 2 | 0.06 |
| 4308 | Ernestine Killer | 1 | 1 | 12 | 2 | 0.06 |
| 4309 | Francesco Lachmann-Ruppert | 1 | 1 | 12 | 2 | 0.06 |
| 4310 | Frédérique Traore | 1 | 1 | 12 | 2 | 0.06 |
| 4311 | Grant Coleman | 1 | 1 | 12 | 2 | 0.06 |
| 4312 | Gregory Frost | 1 | 1 | 12 | 2 | 0.06 |
| 4313 | Hans-J. Hendriks | 1 | 1 | 12 | 2 | 0.06 |
| 4314 | Herr Robin Drewes | 1 | 1 | 12 | 2 | 0.06 |
| 4315 | Isaac Lamb | 1 | 1 | 12 | 2 | 0.06 |
| 4316 | James Rodriguez | 1 | 1 | 12 | 2 | 0.06 |
| 4317 | James Smith | 1 | 1 | 12 | 2 | 0.06 |
| 4318 | John Shaw | 1 | 1 | 12 | 2 | 0.06 |
| 4319 | Johnny Walker | 1 | 1 | 12 | 2 | 0.06 |
| 4320 | Juan Liao | 1 | 1 | 12 | 2 | 0.06 |
| 4321 | Kenneth Lee | 1 | 1 | 12 | 2 | 0.06 |
| 4322 | Kristin Sullivan | 1 | 1 | 12 | 2 | 0.06 |
| 4323 | Laura Mann | 1 | 1 | 12 | 2 | 0.06 |
| 4324 | Lei Yin | 1 | 1 | 12 | 2 | 0.06 |
| 4325 | Lioba Vollbrecht | 1 | 1 | 12 | 2 | 0.06 |
| 4326 | Lisa Peterson | 1 | 1 | 12 | 2 | 0.06 |
| 4327 | Luciano Chindamo | 1 | 1 | 12 | 2 | 0.06 |
| 4328 | Marlene Juncken | 1 | 1 | 12 | 2 | 0.06 |
| 4329 | Mikako Kondo | 1 | 1 | 12 | 2 | 0.06 |
| 4330 | Miss Brandi Torres | 1 | 1 | 12 | 2 | 0.06 |
| 4331 | Momoko Yamamoto | 1 | 1 | 12 | 2 | 0.06 |
| 4332 | Osamu Hayashi | 1 | 1 | 12 | 2 | 0.06 |
| 4333 | Richard Reyes | 1 | 1 | 12 | 2 | 0.06 |
| 4334 | Robert Boone | 1 | 1 | 12 | 2 | 0.06 |
| 4335 | Ruth Hernandez | 1 | 1 | 12 | 2 | 0.06 |
| 4336 | Sandra Burke | 1 | 1 | 12 | 2 | 0.06 |
| 4337 | Sarah Rivera | 1 | 1 | 12 | 2 | 0.06 |
| 4338 | Satomi Aoki | 1 | 1 | 12 | 2 | 0.06 |
| 4339 | Shelby Campbell | 1 | 1 | 12 | 2 | 0.06 |
| 4340 | Stacey Armstrong | 1 | 1 | 12 | 2 | 0.06 |
| 4341 | Steve Young | 1 | 1 | 12 | 2 | 0.06 |
| 4342 | Tao Lu | 1 | 1 | 12 | 2 | 0.06 |
| 4343 | Trevor Bass | 1 | 1 | 12 | 2 | 0.06 |
| 4344 | Viktor Kreusel | 1 | 1 | 12 | 2 | 0.06 |
| 4345 | William Miller | 1 | 1 | 12 | 2 | 0.06 |
| 4346 | Xia Cheng | 1 | 1 | 12 | 2 | 0.06 |
| 4347 | Yosuke Ito | 1 | 1 | 12 | 2 | 0.06 |
| 4348 | Iris Moon | 2 | 1 | 3 | 0 | 0.06 |
| 4349 | Luna Skye | 2 | 1 | 3 | 0 | 0.06 |
| 4350 | Max Wilder | 2 | 1 | 3 | 0 | 0.06 |
| 4351 | Nova Blaze | 2 | 1 | 3 | 0 | 0.06 |
| 4352 | Zane Cruz | 2 | 1 | 3 | 0 | 0.06 |
| 4353 | Adam Knox | 1 | 1 | 8 | 3 | 0.06 |
| 4354 | Anaya Butala | 1 | 1 | 8 | 3 | 0.06 |
| 4355 | Caleb Payne | 1 | 1 | 8 | 3 | 0.06 |
| 4356 | Christy Hernandez | 1 | 1 | 8 | 3 | 0.06 |
| 4357 | Elizabeth Dobes | 1 | 1 | 8 | 3 | 0.06 |
| 4358 | Igor Rychcik | 1 | 1 | 8 | 3 | 0.06 |
| 4359 | Jeffrey Ward | 1 | 1 | 8 | 3 | 0.06 |
| 4360 | Jeremy Alvarez | 1 | 1 | 8 | 3 | 0.06 |
| 4361 | John Campbell | 1 | 1 | 8 | 3 | 0.06 |
| 4362 | Joseph Long | 1 | 1 | 8 | 3 | 0.06 |
| 4363 | Lunar Prism | 1 | 1 | 8 | 3 | 0.06 |
| 4364 | Erik Alvarez | 1 | 1 | 19 | 0 | 0.06 |
| 4365 | Gary White | 1 | 1 | 19 | 0 | 0.06 |
| 4366 | Joel Valentine | 1 | 1 | 19 | 0 | 0.06 |
| 4367 | Joseph Buchanan | 1 | 1 | 19 | 0 | 0.06 |
| 4368 | Julie Graves | 1 | 1 | 19 | 0 | 0.06 |
| 4369 | Karen Smith | 1 | 1 | 19 | 0 | 0.06 |
| 4370 | Mario Weeks | 1 | 1 | 19 | 0 | 0.06 |
| 4371 | Mary Ross | 1 | 1 | 19 | 0 | 0.06 |
| 4372 | Nicholas Ortiz | 1 | 1 | 19 | 0 | 0.06 |
| 4373 | Nicole Williams | 1 | 1 | 19 | 0 | 0.06 |
| 4374 | Patrick Thompson | 1 | 1 | 19 | 0 | 0.06 |
| 4375 | Robert Holland | 1 | 1 | 19 | 0 | 0.06 |
| 4376 | Shawn Soto | 1 | 1 | 19 | 0 | 0.06 |
| 4377 | Xavier Kane | 1 | 1 | 19 | 0 | 0.06 |
| 4378 | Amanda Byrd | 1 | 1 | 15 | 1 | 0.06 |
| 4379 | Evelyn Banks | 1 | 1 | 15 | 1 | 0.06 |
| 4380 | Frederick Hicks | 1 | 1 | 15 | 1 | 0.06 |
| 4381 | Gregory Patton | 1 | 1 | 15 | 1 | 0.06 |
| 4382 | Isabella Smith | 1 | 1 | 15 | 1 | 0.06 |
| 4383 | Kari Warren | 1 | 1 | 15 | 1 | 0.06 |
| 4384 | Linus Bonbach | 1 | 1 | 15 | 1 | 0.06 |
| 4385 | Lisa Harris | 1 | 1 | 15 | 1 | 0.06 |
| 4386 | Raimund Wernecke | 1 | 1 | 15 | 1 | 0.06 |
| 4387 | Sabrina Jenkins | 1 | 1 | 15 | 1 | 0.06 |
| 4388 | Sarah Banks | 1 | 1 | 15 | 1 | 0.06 |
| 4389 | Sean Harrison | 1 | 1 | 15 | 1 | 0.06 |
| 4390 | Shelby Contreras | 1 | 1 | 15 | 1 | 0.06 |
| 4391 | Xiulan Guo | 1 | 1 | 15 | 1 | 0.06 |
| 4392 | Yang Qin | 1 | 1 | 15 | 1 | 0.06 |
| 4393 | Alyssa Thompson | 1 | 1 | 11 | 2 | 0.06 |
| 4394 | Anika Behl | 1 | 1 | 11 | 2 | 0.06 |
| 4395 | Anneliese Döhn | 1 | 1 | 11 | 2 | 0.06 |
| 4396 | Benjamin Brown | 1 | 1 | 11 | 2 | 0.06 |
| 4397 | Benjamin Lee | 1 | 1 | 11 | 2 | 0.06 |
| 4398 | Bradley Hamilton | 1 | 1 | 11 | 2 | 0.06 |
| 4399 | Carlos Brown | 1 | 1 | 11 | 2 | 0.06 |
| 4400 | Chris Tate | 1 | 1 | 11 | 2 | 0.06 |
| 4401 | Cosima Mülichen | 1 | 1 | 11 | 2 | 0.06 |
| 4402 | Deborah Wright | 1 | 1 | 11 | 2 | 0.06 |
| 4403 | Eric Williams | 1 | 1 | 11 | 2 | 0.06 |
| 4404 | Eva Seidel | 1 | 1 | 11 | 2 | 0.06 |
| 4405 | Fenna Zwart | 1 | 1 | 11 | 2 | 0.06 |
| 4406 | Gerhild Patberg | 1 | 1 | 11 | 2 | 0.06 |
| 4407 | Hilda Plath | 1 | 1 | 11 | 2 | 0.06 |
| 4408 | Jasmine Lopez | 1 | 1 | 11 | 2 | 0.06 |
| 4409 | Jennifer Brown | 1 | 1 | 11 | 2 | 0.06 |
| 4410 | Jeremi Pronobis | 1 | 1 | 11 | 2 | 0.06 |
| 4411 | Jing Wen | 1 | 1 | 11 | 2 | 0.06 |
| 4412 | Jo Barnes | 1 | 1 | 11 | 2 | 0.06 |
| 4413 | Jonathan Williams | 1 | 1 | 11 | 2 | 0.06 |
| 4414 | Julia Jones | 1 | 1 | 11 | 2 | 0.06 |
| 4415 | Kari Miranda | 1 | 1 | 11 | 2 | 0.06 |
| 4416 | Kathleen Sandoval | 1 | 1 | 11 | 2 | 0.06 |
| 4417 | Keith Clark | 1 | 1 | 11 | 2 | 0.06 |
| 4418 | Kevin Ruiz | 1 | 1 | 11 | 2 | 0.06 |
| 4419 | Kristin Barber | 1 | 1 | 11 | 2 | 0.06 |
| 4420 | Ludger Ladeck | 1 | 1 | 11 | 2 | 0.06 |
| 4421 | Max Howard | 1 | 1 | 11 | 2 | 0.06 |
| 4422 | Melissa Dennis | 1 | 1 | 11 | 2 | 0.06 |
| 4423 | Michael Anderson | 1 | 1 | 11 | 2 | 0.06 |
| 4424 | Michelle Shepard | 1 | 1 | 11 | 2 | 0.06 |
| 4425 | Miranda Gonzales | 1 | 1 | 11 | 2 | 0.06 |
| 4426 | Nakul Agarwal | 1 | 1 | 11 | 2 | 0.06 |
| 4427 | Nataniel Nazarewicz | 1 | 1 | 11 | 2 | 0.06 |
| 4428 | Ninetta Spinelli | 1 | 1 | 11 | 2 | 0.06 |
| 4429 | Paloma Tomaselli | 1 | 1 | 11 | 2 | 0.06 |
| 4430 | Raymond Wright | 1 | 1 | 11 | 2 | 0.06 |
| 4431 | Richard Kennedy | 1 | 1 | 11 | 2 | 0.06 |
| 4432 | Robin Garrett | 1 | 1 | 11 | 2 | 0.06 |
| 4433 | Ronald Marshall | 1 | 1 | 11 | 2 | 0.06 |
| 4434 | Róża Bełz | 1 | 1 | 11 | 2 | 0.06 |
| 4435 | Sabrina Jimenez | 1 | 1 | 11 | 2 | 0.06 |
| 4436 | Sahil Basak | 1 | 1 | 11 | 2 | 0.06 |
| 4437 | Stephanie Frank | 1 | 1 | 11 | 2 | 0.06 |
| 4438 | Sylvia Thompson | 1 | 1 | 11 | 2 | 0.06 |
| 4439 | Taylor Reed | 1 | 1 | 11 | 2 | 0.06 |
| 4440 | Valentine Peukert | 1 | 1 | 11 | 2 | 0.06 |
| 4441 | Valerie Miller | 1 | 1 | 11 | 2 | 0.06 |
| 4442 | Yang Hao | 1 | 1 | 11 | 2 | 0.06 |
| 4443 | Benjamin Clark | 3 | 0 | 3 | 0 | 0.06 |
| 4444 | Maximus Grey | 3 | 0 | 3 | 0 | 0.06 |
| 4445 | Sophia Brooks | 3 | 0 | 3 | 0 | 0.06 |
| 4446 | Quinn Rivers | 2 | 1 | 2 | 0 | 0.06 |
| 4447 | Ryder Lyons | 2 | 1 | 2 | 0 | 0.06 |
| 4448 | Xiuying Tan | 2 | 1 | 2 | 0 | 0.06 |
| 4449 | Lunar Echo | 1 | 1 | 7 | 3 | 0.06 |
| 4450 | Maaya Ishikawa | 1 | 1 | 7 | 3 | 0.06 |
| 4451 | Paul Dunn | 1 | 1 | 7 | 3 | 0.06 |
| 4452 | Sayuri Kondo | 1 | 1 | 7 | 3 | 0.06 |
| 4453 | Torsten Etzold | 1 | 1 | 7 | 3 | 0.06 |
| 4454 | Veronica Bell | 1 | 1 | 7 | 3 | 0.06 |
| 4455 | Yui Ito | 1 | 1 | 7 | 3 | 0.06 |
| 4456 | Amy Powell | 1 | 1 | 14 | 1 | 0.06 |
| 4457 | Angela Thomas | 1 | 1 | 14 | 1 | 0.06 |
| 4458 | Angela Villa | 1 | 1 | 14 | 1 | 0.06 |
| 4459 | Carol Simpson | 1 | 1 | 14 | 1 | 0.06 |
| 4460 | Cassidy Hubbard | 1 | 1 | 14 | 1 | 0.06 |
| 4461 | Debra Graham | 1 | 1 | 14 | 1 | 0.06 |
| 4462 | Donna Hanson | 1 | 1 | 14 | 1 | 0.06 |
| 4463 | Dylan Schwartz | 1 | 1 | 14 | 1 | 0.06 |
| 4464 | Edward Evans | 1 | 1 | 14 | 1 | 0.06 |
| 4465 | Erika Ruiz | 1 | 1 | 14 | 1 | 0.06 |
| 4466 | Heather Cabrera | 1 | 1 | 14 | 1 | 0.06 |
| 4467 | James Aguilar | 1 | 1 | 14 | 1 | 0.06 |
| 4468 | James Henderson | 1 | 1 | 14 | 1 | 0.06 |
| 4469 | Joel Long | 1 | 1 | 14 | 1 | 0.06 |
| 4470 | Jörg-Peter Hecker | 1 | 1 | 14 | 1 | 0.06 |
| 4471 | Katherine Johnston | 1 | 1 | 14 | 1 | 0.06 |
| 4472 | Kelly Castro | 1 | 1 | 14 | 1 | 0.06 |
| 4473 | Laura Gordon | 1 | 1 | 14 | 1 | 0.06 |
| 4474 | Melissa Arias | 1 | 1 | 14 | 1 | 0.06 |
| 4475 | Michael Nixon | 1 | 1 | 14 | 1 | 0.06 |
| 4476 | Midnight Prism | 1 | 1 | 14 | 1 | 0.06 |
| 4477 | Milica Textor-Sorgatz | 1 | 1 | 14 | 1 | 0.06 |
| 4478 | Nathan Jones | 1 | 1 | 14 | 1 | 0.06 |
| 4479 | Oliver Henschel | 1 | 1 | 14 | 1 | 0.06 |
| 4480 | Patrick Cook | 1 | 1 | 14 | 1 | 0.06 |
| 4481 | Ryan Leblanc | 1 | 1 | 14 | 1 | 0.06 |
| 4482 | Shawn Johnson | 1 | 1 | 14 | 1 | 0.06 |
| 4483 | Stanley Hamilton | 1 | 1 | 14 | 1 | 0.06 |
| 4484 | Stephen Lawrence | 1 | 1 | 14 | 1 | 0.06 |
| 4485 | Susan Christian | 1 | 1 | 14 | 1 | 0.06 |
| 4486 | Terri Reynolds | 1 | 1 | 14 | 1 | 0.06 |
| 4487 | Ayse Häring | 1 | 1 | 10 | 2 | 0.06 |
| 4488 | Christina Smith | 1 | 1 | 10 | 2 | 0.06 |
| 4489 | Courtney Bennett | 1 | 1 | 10 | 2 | 0.06 |
| 4490 | Gisa Hettner-Adler | 1 | 1 | 10 | 2 | 0.06 |
| 4491 | Gloria Gutknecht | 1 | 1 | 10 | 2 | 0.06 |
| 4492 | Jie Han | 1 | 1 | 10 | 2 | 0.06 |
| 4493 | Jose Garrett | 1 | 1 | 10 | 2 | 0.06 |
| 4494 | Lori Martin | 1 | 1 | 10 | 2 | 0.06 |
| 4495 | Pierre Ruppert | 1 | 1 | 10 | 2 | 0.06 |
| 4496 | Qiang Hu | 1 | 1 | 10 | 2 | 0.06 |
| 4497 | Robert Combs | 1 | 1 | 10 | 2 | 0.06 |
| 4498 | The Omega Collective | 1 | 1 | 10 | 2 | 0.06 |
| 4499 | Theodore Shaw | 1 | 1 | 10 | 2 | 0.06 |
| 4500 | William Tyler | 1 | 1 | 10 | 2 | 0.06 |
| 4501 | Xia Zou | 1 | 1 | 10 | 2 | 0.06 |
| 4502 | Antoinette Bertin | 1 | 1 | 6 | 3 | 0.06 |
| 4503 | Cynthia Hayes | 1 | 1 | 6 | 3 | 0.06 |
| 4504 | Kimberly Keller | 1 | 1 | 6 | 3 | 0.06 |
| 4505 | Ping Zhu | 1 | 1 | 6 | 3 | 0.06 |
| 4506 | Ronnie Rodriguez | 1 | 1 | 6 | 3 | 0.06 |
| 4507 | Yang Tian | 1 | 1 | 6 | 3 | 0.06 |
| 4508 | Alfredo del Pujol | 1 | 1 | 13 | 1 | 0.06 |
| 4509 | Amancio Delgado Morata | 1 | 1 | 13 | 1 | 0.06 |
| 4510 | Amanda Reyes | 1 | 1 | 13 | 1 | 0.06 |
| 4511 | Antonio Allen | 1 | 1 | 13 | 1 | 0.06 |
| 4512 | Ariel Falcó Narváez | 1 | 1 | 13 | 1 | 0.06 |
| 4513 | Arthur Colas | 1 | 1 | 13 | 1 | 0.06 |
| 4514 | Bartolomeo Castellitto-Gritti | 1 | 1 | 13 | 1 | 0.06 |
| 4515 | Benvenuto Castiglione-Pulci | 1 | 1 | 13 | 1 | 0.06 |
| 4516 | Borja Santamaria-Adán | 1 | 1 | 13 | 1 | 0.06 |
| 4517 | Corinna Schweitzer | 1 | 1 | 13 | 1 | 0.06 |
| 4518 | Daniel Martin | 1 | 1 | 13 | 1 | 0.06 |
| 4519 | Dylan Williams | 1 | 1 | 13 | 1 | 0.06 |
| 4520 | Elizabeth Adams | 1 | 1 | 13 | 1 | 0.06 |
| 4521 | Erin Hall | 1 | 1 | 13 | 1 | 0.06 |
| 4522 | Eveline Gotthard | 1 | 1 | 13 | 1 | 0.06 |
| 4523 | Fabiana Narváez Vazquez | 1 | 1 | 13 | 1 | 0.06 |
| 4524 | Gang Shi | 1 | 1 | 13 | 1 | 0.06 |
| 4525 | Geronimo Lamborghini-Dossetti | 1 | 1 | 13 | 1 | 0.06 |
| 4526 | Gioele Merisi | 1 | 1 | 13 | 1 | 0.06 |
| 4527 | Giuliano Anastasi | 1 | 1 | 13 | 1 | 0.06 |
| 4528 | Hans-Karl Schottin | 1 | 1 | 13 | 1 | 0.06 |
| 4529 | Hermann Josef Matthäi | 1 | 1 | 13 | 1 | 0.06 |
| 4530 | Jennifer Curtis | 1 | 1 | 13 | 1 | 0.06 |
| 4531 | Jessica Phelps | 1 | 1 | 13 | 1 | 0.06 |
| 4532 | Jessica Smith | 1 | 1 | 13 | 1 | 0.06 |
| 4533 | Joseph Nichols | 1 | 1 | 13 | 1 | 0.06 |
| 4534 | Kara Rich | 1 | 1 | 13 | 1 | 0.06 |
| 4535 | Katherine Olson | 1 | 1 | 13 | 1 | 0.06 |
| 4536 | Kati Sauer-Rudolph | 1 | 1 | 13 | 1 | 0.06 |
| 4537 | Kim Washington | 1 | 1 | 13 | 1 | 0.06 |
| 4538 | Krista Dunn | 1 | 1 | 13 | 1 | 0.06 |
| 4539 | Luciano Maderna | 1 | 1 | 13 | 1 | 0.06 |
| 4540 | Mandy Hood | 1 | 1 | 13 | 1 | 0.06 |
| 4541 | Marc Ward | 1 | 1 | 13 | 1 | 0.06 |
| 4542 | Maria Morris | 1 | 1 | 13 | 1 | 0.06 |
| 4543 | Matthew Walker | 1 | 1 | 13 | 1 | 0.06 |
| 4544 | Mayte Salvà Durán | 1 | 1 | 13 | 1 | 0.06 |
| 4545 | Melanie Armstrong | 1 | 1 | 13 | 1 | 0.06 |
| 4546 | Melissa Merritt | 1 | 1 | 13 | 1 | 0.06 |
| 4547 | Michelle Anderson | 1 | 1 | 13 | 1 | 0.06 |
| 4548 | Mohamed Cazorla | 1 | 1 | 13 | 1 | 0.06 |
| 4549 | Naoko Miura | 1 | 1 | 13 | 1 | 0.06 |
| 4550 | Nico Castellanos García | 1 | 1 | 13 | 1 | 0.06 |
| 4551 | Paola Condoleo | 1 | 1 | 13 | 1 | 0.06 |
| 4552 | Paula Mendizábal Alegria | 1 | 1 | 13 | 1 | 0.06 |
| 4553 | Renata Parpinel | 1 | 1 | 13 | 1 | 0.06 |
| 4554 | Robert Villanueva | 1 | 1 | 13 | 1 | 0.06 |
| 4555 | Rodolfo Cutuli | 1 | 1 | 13 | 1 | 0.06 |
| 4556 | Rosario Pujadas Barceló | 1 | 1 | 13 | 1 | 0.06 |
| 4557 | Sharon Crawford | 1 | 1 | 13 | 1 | 0.06 |
| 4558 | Silvio Frías Castejón | 1 | 1 | 13 | 1 | 0.06 |
| 4559 | Stephanie House | 1 | 1 | 13 | 1 | 0.06 |
| 4560 | Terri Thomas | 1 | 1 | 13 | 1 | 0.06 |
| 4561 | Wei Yang | 1 | 1 | 13 | 1 | 0.06 |
| 4562 | Yang Mao | 1 | 1 | 13 | 1 | 0.06 |
| 4563 | Alexandra Moreno | 1 | 1 | 9 | 2 | 0.06 |
| 4564 | Amico Luciani | 1 | 1 | 9 | 2 | 0.06 |
| 4565 | Anna Vávrová | 1 | 1 | 9 | 2 | 0.06 |
| 4566 | Ashley Robinson | 1 | 1 | 9 | 2 | 0.06 |
| 4567 | Caleb Ross | 1 | 1 | 9 | 2 | 0.06 |
| 4568 | Christine Turner | 1 | 1 | 9 | 2 | 0.06 |
| 4569 | Courtney Castillo | 1 | 1 | 9 | 2 | 0.06 |
| 4570 | David Reese | 1 | 1 | 9 | 2 | 0.06 |
| 4571 | David White | 1 | 1 | 9 | 2 | 0.06 |
| 4572 | Elmo Calbo | 1 | 1 | 9 | 2 | 0.06 |
| 4573 | Gary Stephens | 1 | 1 | 9 | 2 | 0.06 |
| 4574 | Jennifer Davis | 1 | 1 | 9 | 2 | 0.06 |
| 4575 | Jun Tao | 1 | 1 | 9 | 2 | 0.06 |
| 4576 | Karsten Löwer | 1 | 1 | 9 | 2 | 0.06 |
| 4577 | Katie Oliver | 1 | 1 | 9 | 2 | 0.06 |
| 4578 | Keith Stone | 1 | 1 | 9 | 2 | 0.06 |
| 4579 | Kelli Jackson | 1 | 1 | 9 | 2 | 0.06 |
| 4580 | Li Dai | 1 | 1 | 9 | 2 | 0.06 |
| 4581 | Mackenzie Greene | 1 | 1 | 9 | 2 | 0.06 |
| 4582 | Mary Combs | 1 | 1 | 9 | 2 | 0.06 |
| 4583 | Matthieu-Daniel Launay | 1 | 1 | 9 | 2 | 0.06 |
| 4584 | Megan Bridges | 1 | 1 | 9 | 2 | 0.06 |
| 4585 | Nancy Mitchell | 1 | 1 | 9 | 2 | 0.06 |
| 4586 | Nicholas Porter | 1 | 1 | 9 | 2 | 0.06 |
| 4587 | Nick Kensy | 1 | 1 | 9 | 2 | 0.06 |
| 4588 | Nicolas Jones | 1 | 1 | 9 | 2 | 0.06 |
| 4589 | Nicole Bass | 1 | 1 | 9 | 2 | 0.06 |
| 4590 | Richard Gonzales | 1 | 1 | 9 | 2 | 0.06 |
| 4591 | Richard Kovář | 1 | 1 | 9 | 2 | 0.06 |
| 4592 | Ronnie Watkins | 1 | 1 | 9 | 2 | 0.06 |
| 4593 | Ryan Dunlap | 1 | 1 | 9 | 2 | 0.06 |
| 4594 | Saira Sood | 1 | 1 | 9 | 2 | 0.06 |
| 4595 | Sean King | 1 | 1 | 9 | 2 | 0.06 |
| 4596 | Shelly Lewis | 1 | 1 | 9 | 2 | 0.06 |
| 4597 | Stefanie Sullivan | 1 | 1 | 9 | 2 | 0.06 |
| 4598 | Thérèse Guillou | 1 | 1 | 9 | 2 | 0.06 |
| 4599 | Tristan Chauveau | 1 | 1 | 9 | 2 | 0.06 |
| 4600 | Warren Fleming | 1 | 1 | 9 | 2 | 0.06 |
| 4601 | Xiuying Jia | 1 | 1 | 9 | 2 | 0.06 |
| 4602 | Yves Aubry | 1 | 1 | 9 | 2 | 0.06 |
| 4603 | Bianca Singleton | 1 | 1 | 5 | 3 | 0.06 |
| 4604 | Brianna Norris | 1 | 1 | 5 | 3 | 0.06 |
| 4605 | Elias Rouwenhorst | 1 | 1 | 5 | 3 | 0.06 |
| 4606 | Erin Smith | 1 | 1 | 5 | 3 | 0.06 |
| 4607 | Igor Dyś | 1 | 1 | 5 | 3 | 0.06 |
| 4608 | Jérôme Riou | 1 | 1 | 5 | 3 | 0.06 |
| 4609 | Michelle Laurent de la Berger | 1 | 1 | 5 | 3 | 0.06 |
| 4610 | Nicholas Burns | 1 | 1 | 5 | 3 | 0.06 |
| 4611 | Teresa Bohlander | 1 | 1 | 5 | 3 | 0.06 |
| 4612 | Aaron Livingston | 1 | 1 | 12 | 1 | 0.05 |
| 4613 | Aleksandar Kohl | 1 | 1 | 12 | 1 | 0.05 |
| 4614 | Anay Behl | 1 | 1 | 12 | 1 | 0.05 |
| 4615 | Angelica Reid | 1 | 1 | 12 | 1 | 0.05 |
| 4616 | Atenulf Nadi-Vergassola | 1 | 1 | 12 | 1 | 0.05 |
| 4617 | Brittany Mueller | 1 | 1 | 12 | 1 | 0.05 |
| 4618 | Cassandra Carroll | 1 | 1 | 12 | 1 | 0.05 |
| 4619 | Chad Chavez | 1 | 1 | 12 | 1 | 0.05 |
| 4620 | David Duncan | 1 | 1 | 12 | 1 | 0.05 |
| 4621 | Emily Sullivan | 1 | 1 | 12 | 1 | 0.05 |
| 4622 | Eric Morrison | 1 | 1 | 12 | 1 | 0.05 |
| 4623 | Fabrizia Gualtieri | 1 | 1 | 12 | 1 | 0.05 |
| 4624 | Folker Jacob-Kreusel | 1 | 1 | 12 | 1 | 0.05 |
| 4625 | Francis Kaufman | 1 | 1 | 12 | 1 | 0.05 |
| 4626 | Francisco Kerr | 1 | 1 | 12 | 1 | 0.05 |
| 4627 | Gail Garrett | 1 | 1 | 12 | 1 | 0.05 |
| 4628 | Hanako Takahashi | 1 | 1 | 12 | 1 | 0.05 |
| 4629 | Holly Young | 1 | 1 | 12 | 1 | 0.05 |
| 4630 | Jie Qin | 1 | 1 | 12 | 1 | 0.05 |
| 4631 | Johanne Salz | 1 | 1 | 12 | 1 | 0.05 |
| 4632 | Joseph Preston | 1 | 1 | 12 | 1 | 0.05 |
| 4633 | Joshua Cobb | 1 | 1 | 12 | 1 | 0.05 |
| 4634 | Kana Hashimoto | 1 | 1 | 12 | 1 | 0.05 |
| 4635 | Kimberly Martin | 1 | 1 | 12 | 1 | 0.05 |
| 4636 | Maria-Luise Flantz | 1 | 1 | 12 | 1 | 0.05 |
| 4637 | Marissa Holt | 1 | 1 | 12 | 1 | 0.05 |
| 4638 | Matthew Adams | 1 | 1 | 12 | 1 | 0.05 |
| 4639 | Michael Hill | 1 | 1 | 12 | 1 | 0.05 |
| 4640 | Miss Stephanie Middleton | 1 | 1 | 12 | 1 | 0.05 |
| 4641 | Monique Jefferson | 1 | 1 | 12 | 1 | 0.05 |
| 4642 | Nidia Menéndez Mateo | 1 | 1 | 12 | 1 | 0.05 |
| 4643 | Pedro Scholtz | 1 | 1 | 12 | 1 | 0.05 |
| 4644 | Rachael Stafford | 1 | 1 | 12 | 1 | 0.05 |
| 4645 | Richard White | 1 | 1 | 12 | 1 | 0.05 |
| 4646 | Robert Cowan | 1 | 1 | 12 | 1 | 0.05 |
| 4647 | Sarah Phillips | 1 | 1 | 12 | 1 | 0.05 |
| 4648 | Sarah Wright | 1 | 1 | 12 | 1 | 0.05 |
| 4649 | Shamik Jhaveri | 1 | 1 | 12 | 1 | 0.05 |
| 4650 | Tracey Murphy | 1 | 1 | 12 | 1 | 0.05 |
| 4651 | Vitus Heinz | 1 | 1 | 12 | 1 | 0.05 |
| 4652 | William Chan | 1 | 1 | 12 | 1 | 0.05 |
| 4653 | Zara Dugar | 1 | 1 | 12 | 1 | 0.05 |
| 4654 | Andrew Peters | 1 | 1 | 8 | 2 | 0.05 |
| 4655 | Audrey Le Boucher | 1 | 1 | 8 | 2 | 0.05 |
| 4656 | Benoît Delmas | 1 | 1 | 8 | 2 | 0.05 |
| 4657 | Donald Cooper | 1 | 1 | 8 | 2 | 0.05 |
| 4658 | Erika Austin | 1 | 1 | 8 | 2 | 0.05 |
| 4659 | Henny Caspar | 1 | 1 | 8 | 2 | 0.05 |
| 4660 | Justus Hornig | 1 | 1 | 8 | 2 | 0.05 |
| 4661 | Kornelia Pędzik | 1 | 1 | 8 | 2 | 0.05 |
| 4662 | Manon Diaz | 1 | 1 | 8 | 2 | 0.05 |
| 4663 | Rika Tanaka | 1 | 1 | 8 | 2 | 0.05 |
| 4664 | Robert Johnson | 1 | 1 | 8 | 2 | 0.05 |
| 4665 | Travis Gonzales | 1 | 1 | 8 | 2 | 0.05 |
| 4666 | Melissa Lucero | 1 | 0 | 14 | 5 | 0.05 |
| 4667 | Thomas Lee | 1 | 0 | 14 | 5 | 0.05 |
| 4668 | Vít Svoboda | 1 | 0 | 14 | 5 | 0.05 |
| 4669 | Daisy Rose | 1 | 0 | 25 | 2 | 0.05 |
| 4670 | Mark West | 1 | 0 | 25 | 2 | 0.05 |
| 4671 | Sara Johnson | 1 | 0 | 25 | 2 | 0.05 |
| 4672 | Stephanie Andersen | 1 | 0 | 25 | 2 | 0.05 |
| 4673 | Tiffany Simmons | 1 | 0 | 25 | 2 | 0.05 |
| 4674 | Aaron Young | 1 | 1 | 15 | 0 | 0.05 |
| 4675 | Benjamin Moore | 1 | 1 | 15 | 0 | 0.05 |
| 4676 | Connor Lopez | 1 | 1 | 15 | 0 | 0.05 |
| 4677 | Fang Kang | 1 | 1 | 15 | 0 | 0.05 |
| 4678 | Haley Joseph | 1 | 1 | 15 | 0 | 0.05 |
| 4679 | Hannah Roberson | 1 | 1 | 15 | 0 | 0.05 |
| 4680 | Mike Rose | 1 | 1 | 15 | 0 | 0.05 |
| 4681 | Ming Yin | 1 | 1 | 15 | 0 | 0.05 |
| 4682 | Robert Rollins | 1 | 1 | 15 | 0 | 0.05 |
| 4683 | Robin Noble | 1 | 1 | 15 | 0 | 0.05 |
| 4684 | Timothy Scott | 1 | 1 | 15 | 0 | 0.05 |
| 4685 | Alexis Hawkins | 1 | 1 | 11 | 1 | 0.05 |
| 4686 | Alfio Greggio | 1 | 1 | 11 | 1 | 0.05 |
| 4687 | Alina Ricciardi | 1 | 1 | 11 | 1 | 0.05 |
| 4688 | Andrea Martin | 1 | 1 | 11 | 1 | 0.05 |
| 4689 | Angel Henderson | 1 | 1 | 11 | 1 | 0.05 |
| 4690 | Ashley Waters | 1 | 1 | 11 | 1 | 0.05 |
| 4691 | Atenulf Pigafetta | 1 | 1 | 11 | 1 | 0.05 |
| 4692 | Audrey King | 1 | 1 | 11 | 1 | 0.05 |
| 4693 | Bobby Guzman | 1 | 1 | 11 | 1 | 0.05 |
| 4694 | Bruno Silvestri | 1 | 1 | 11 | 1 | 0.05 |
| 4695 | Calixta Moya Gómez | 1 | 1 | 11 | 1 | 0.05 |
| 4696 | Christopher Aguilar | 1 | 1 | 11 | 1 | 0.05 |
| 4697 | Cipriano Navone | 1 | 1 | 11 | 1 | 0.05 |
| 4698 | Craig Ortega | 1 | 1 | 11 | 1 | 0.05 |
| 4699 | Danielle Martin | 1 | 1 | 11 | 1 | 0.05 |
| 4700 | Devin Mccoy | 1 | 1 | 11 | 1 | 0.05 |
| 4701 | Erin Kim | 1 | 1 | 11 | 1 | 0.05 |
| 4702 | Erin Moses | 1 | 1 | 11 | 1 | 0.05 |
| 4703 | Eva Squarcione | 1 | 1 | 11 | 1 | 0.05 |
| 4704 | Fang Zhao | 1 | 1 | 11 | 1 | 0.05 |
| 4705 | Gilberto Cainero | 1 | 1 | 11 | 1 | 0.05 |
| 4706 | Hannah Garrett | 1 | 1 | 11 | 1 | 0.05 |
| 4707 | Heather Miller | 1 | 1 | 11 | 1 | 0.05 |
| 4708 | James Torres | 1 | 1 | 11 | 1 | 0.05 |
| 4709 | Jing Cheng | 1 | 1 | 11 | 1 | 0.05 |
| 4710 | Jing Fan | 1 | 1 | 11 | 1 | 0.05 |
| 4711 | Jing Zeng | 1 | 1 | 11 | 1 | 0.05 |
| 4712 | Jonathan Vasquez | 1 | 1 | 11 | 1 | 0.05 |
| 4713 | Jose White | 1 | 1 | 11 | 1 | 0.05 |
| 4714 | Juanito Jimenez Hernández | 1 | 1 | 11 | 1 | 0.05 |
| 4715 | Kaitlin Davis | 1 | 1 | 11 | 1 | 0.05 |
| 4716 | Kaori Ito | 1 | 1 | 11 | 1 | 0.05 |
| 4717 | Katrina Maynard | 1 | 1 | 11 | 1 | 0.05 |
| 4718 | Kenneth Johnson | 1 | 1 | 11 | 1 | 0.05 |
| 4719 | Kimberly Miles | 1 | 1 | 11 | 1 | 0.05 |
| 4720 | Kristine Bullock | 1 | 1 | 11 | 1 | 0.05 |
| 4721 | Li Yan | 1 | 1 | 11 | 1 | 0.05 |
| 4722 | Luke Murray | 1 | 1 | 11 | 1 | 0.05 |
| 4723 | Manfred Schmiedecke | 1 | 1 | 11 | 1 | 0.05 |
| 4724 | Mariana Galeati | 1 | 1 | 11 | 1 | 0.05 |
| 4725 | Mary Anthony | 1 | 1 | 11 | 1 | 0.05 |
| 4726 | Micheal Mcguire | 1 | 1 | 11 | 1 | 0.05 |
| 4727 | Na Gong | 1 | 1 | 11 | 1 | 0.05 |
| 4728 | Naoko Sato | 1 | 1 | 11 | 1 | 0.05 |
| 4729 | Olivia Ortega Bermejo | 1 | 1 | 11 | 1 | 0.05 |
| 4730 | Qiang Yao | 1 | 1 | 11 | 1 | 0.05 |
| 4731 | Rachel Curry | 1 | 1 | 11 | 1 | 0.05 |
| 4732 | Raffaello Tarchetti | 1 | 1 | 11 | 1 | 0.05 |
| 4733 | Samantha Andrews | 1 | 1 | 11 | 1 | 0.05 |
| 4734 | Samantha Dawson | 1 | 1 | 11 | 1 | 0.05 |
| 4735 | Sandy Ray | 1 | 1 | 11 | 1 | 0.05 |
| 4736 | Susan Young | 1 | 1 | 11 | 1 | 0.05 |
| 4737 | Virginia Ford | 1 | 1 | 11 | 1 | 0.05 |
| 4738 | Xiuying Lei | 1 | 1 | 11 | 1 | 0.05 |
| 4739 | Yoko Hashimoto | 1 | 1 | 11 | 1 | 0.05 |
| 4740 | Adrien Gonzalez-Duval | 1 | 1 | 7 | 2 | 0.05 |
| 4741 | Alessandra Omma-Paolini | 1 | 1 | 7 | 2 | 0.05 |
| 4742 | Alexis Griffith | 1 | 1 | 7 | 2 | 0.05 |
| 4743 | Amanda Kennedy | 1 | 1 | 7 | 2 | 0.05 |
| 4744 | Anastazja Brózda | 1 | 1 | 7 | 2 | 0.05 |
| 4745 | Andrea Hamilton | 1 | 1 | 7 | 2 | 0.05 |
| 4746 | Andrzej Kamyszek | 1 | 1 | 7 | 2 | 0.05 |
| 4747 | Angela Fisher | 1 | 1 | 7 | 2 | 0.05 |
| 4748 | Antoine Blanc | 1 | 1 | 7 | 2 | 0.05 |
| 4749 | Audrey Picard | 1 | 1 | 7 | 2 | 0.05 |
| 4750 | Carrie Lee | 1 | 1 | 7 | 2 | 0.05 |
| 4751 | Christina Cunningham | 1 | 1 | 7 | 2 | 0.05 |
| 4752 | Ehrenfried Werner | 1 | 1 | 7 | 2 | 0.05 |
| 4753 | Erik Sharp | 1 | 1 | 7 | 2 | 0.05 |
| 4754 | Felicia Gilbert | 1 | 1 | 7 | 2 | 0.05 |
| 4755 | Franciszek Wieja | 1 | 1 | 7 | 2 | 0.05 |
| 4756 | Frederick Houston | 1 | 1 | 7 | 2 | 0.05 |
| 4757 | Guy Arnaud | 1 | 1 | 7 | 2 | 0.05 |
| 4758 | Hannah Newton | 1 | 1 | 7 | 2 | 0.05 |
| 4759 | Hellmut Graf | 1 | 1 | 7 | 2 | 0.05 |
| 4760 | Jivika Dar | 1 | 1 | 7 | 2 | 0.05 |
| 4761 | Kelly Carpenter | 1 | 1 | 7 | 2 | 0.05 |
| 4762 | Kimberly Howe | 1 | 1 | 7 | 2 | 0.05 |
| 4763 | Lauren Brown | 1 | 1 | 7 | 2 | 0.05 |
| 4764 | Lauren Turner | 1 | 1 | 7 | 2 | 0.05 |
| 4765 | Marcelina Wochnik | 1 | 1 | 7 | 2 | 0.05 |
| 4766 | Mary Frank | 1 | 1 | 7 | 2 | 0.05 |
| 4767 | Maryse-Margaux Pinto | 1 | 1 | 7 | 2 | 0.05 |
| 4768 | Megan Franklin | 1 | 1 | 7 | 2 | 0.05 |
| 4769 | Michael Jacobson | 1 | 1 | 7 | 2 | 0.05 |
| 4770 | Nancy Dunlap | 1 | 1 | 7 | 2 | 0.05 |
| 4771 | Natalie Fields | 1 | 1 | 7 | 2 | 0.05 |
| 4772 | Nicole Lee | 1 | 1 | 7 | 2 | 0.05 |
| 4773 | Paul Hughes | 1 | 1 | 7 | 2 | 0.05 |
| 4774 | Rico Weimer | 1 | 1 | 7 | 2 | 0.05 |
| 4775 | Rika Shimizu | 1 | 1 | 7 | 2 | 0.05 |
| 4776 | Robert Velasquez | 1 | 1 | 7 | 2 | 0.05 |
| 4777 | Sandra Hunter | 1 | 1 | 7 | 2 | 0.05 |
| 4778 | Shannon White | 1 | 1 | 7 | 2 | 0.05 |
| 4779 | Stephanie Allen | 1 | 1 | 7 | 2 | 0.05 |
| 4780 | Theresa Webster | 1 | 1 | 7 | 2 | 0.05 |
| 4781 | Todd Lopez | 1 | 1 | 7 | 2 | 0.05 |
| 4782 | Whitney Yates | 1 | 1 | 7 | 2 | 0.05 |
| 4783 | Andrew Coleman | 1 | 1 | 14 | 0 | 0.05 |
| 4784 | Austin Robinson | 1 | 1 | 14 | 0 | 0.05 |
| 4785 | Carlo Altera | 1 | 1 | 14 | 0 | 0.05 |
| 4786 | Dariusz Trupp | 1 | 1 | 14 | 0 | 0.05 |
| 4787 | Emilio Missoni | 1 | 1 | 14 | 0 | 0.05 |
| 4788 | Federigo Satta | 1 | 1 | 14 | 0 | 0.05 |
| 4789 | Felicia Walton | 1 | 1 | 14 | 0 | 0.05 |
| 4790 | Giovanna Tirabassi | 1 | 1 | 14 | 0 | 0.05 |
| 4791 | Hugo Visconti | 1 | 1 | 14 | 0 | 0.05 |
| 4792 | Jaroslav Putz | 1 | 1 | 14 | 0 | 0.05 |
| 4793 | Jens-Uwe Pruschke | 1 | 1 | 14 | 0 | 0.05 |
| 4794 | Joe Humphrey | 1 | 1 | 14 | 0 | 0.05 |
| 4795 | Kathleen Sutton | 1 | 1 | 14 | 0 | 0.05 |
| 4796 | Kayla Gonzales | 1 | 1 | 14 | 0 | 0.05 |
| 4797 | Lorenzo Baresi | 1 | 1 | 14 | 0 | 0.05 |
| 4798 | Ludmila Wesack | 1 | 1 | 14 | 0 | 0.05 |
| 4799 | Maria Zola | 1 | 1 | 14 | 0 | 0.05 |
| 4800 | Nicholas Swanson | 1 | 1 | 14 | 0 | 0.05 |
| 4801 | Olivia Steinberg | 1 | 1 | 14 | 0 | 0.05 |
| 4802 | Patrick Howard | 1 | 1 | 14 | 0 | 0.05 |
| 4803 | Susan Scott | 1 | 1 | 14 | 0 | 0.05 |
| 4804 | Terri Chapman | 1 | 1 | 14 | 0 | 0.05 |
| 4805 | Vanessa Villadicani | 1 | 1 | 14 | 0 | 0.05 |
| 4806 | Alejandro Barnes | 1 | 1 | 10 | 1 | 0.05 |
| 4807 | Alexa Brown | 1 | 1 | 10 | 1 | 0.05 |
| 4808 | Alexander Budig | 1 | 1 | 10 | 1 | 0.05 |
| 4809 | Aniela Chojna | 1 | 1 | 10 | 1 | 0.05 |
| 4810 | Ashley Bennett | 1 | 1 | 10 | 1 | 0.05 |
| 4811 | Betty Faulkner | 1 | 1 | 10 | 1 | 0.05 |
| 4812 | Brian Anderson | 1 | 1 | 10 | 1 | 0.05 |
| 4813 | Charles Paul | 1 | 1 | 10 | 1 | 0.05 |
| 4814 | Chase Andrews | 1 | 1 | 10 | 1 | 0.05 |
| 4815 | Christopher Wilcox | 1 | 1 | 10 | 1 | 0.05 |
| 4816 | Christy Lewis | 1 | 1 | 10 | 1 | 0.05 |
| 4817 | Daniel Cross | 1 | 1 | 10 | 1 | 0.05 |
| 4818 | Daniel Miller | 1 | 1 | 10 | 1 | 0.05 |
| 4819 | David Glenn | 1 | 1 | 10 | 1 | 0.05 |
| 4820 | Delia Hesse-Wulf | 1 | 1 | 10 | 1 | 0.05 |
| 4821 | Edwin Diaz | 1 | 1 | 10 | 1 | 0.05 |
| 4822 | Eric Wallace | 1 | 1 | 10 | 1 | 0.05 |
| 4823 | Gang Ding | 1 | 1 | 10 | 1 | 0.05 |
| 4824 | Guenter Stumpf | 1 | 1 | 10 | 1 | 0.05 |
| 4825 | Herr Rudolph Schaaf | 1 | 1 | 10 | 1 | 0.05 |
| 4826 | Jacob Grimes | 1 | 1 | 10 | 1 | 0.05 |
| 4827 | James Cruz | 1 | 1 | 10 | 1 | 0.05 |
| 4828 | James Vaughn | 1 | 1 | 10 | 1 | 0.05 |
| 4829 | James White | 1 | 1 | 10 | 1 | 0.05 |
| 4830 | Janet Cunningham | 1 | 1 | 10 | 1 | 0.05 |
| 4831 | Jasmine Hammond | 1 | 1 | 10 | 1 | 0.05 |
| 4832 | Johnny Smith | 1 | 1 | 10 | 1 | 0.05 |
| 4833 | Jorge Brown | 1 | 1 | 10 | 1 | 0.05 |
| 4834 | Justin Allen | 1 | 1 | 10 | 1 | 0.05 |
| 4835 | Karen Schultz | 1 | 1 | 10 | 1 | 0.05 |
| 4836 | Kevin Simmons | 1 | 1 | 10 | 1 | 0.05 |
| 4837 | Kimberly Knight | 1 | 1 | 10 | 1 | 0.05 |
| 4838 | Kirk Griffin | 1 | 1 | 10 | 1 | 0.05 |
| 4839 | Kyle Myers | 1 | 1 | 10 | 1 | 0.05 |
| 4840 | Linda Chase | 1 | 1 | 10 | 1 | 0.05 |
| 4841 | Lonnie Estrada | 1 | 1 | 10 | 1 | 0.05 |
| 4842 | Louis Brown | 1 | 1 | 10 | 1 | 0.05 |
| 4843 | Mark Stokes | 1 | 1 | 10 | 1 | 0.05 |
| 4844 | Mehmet Junk | 1 | 1 | 10 | 1 | 0.05 |
| 4845 | Melody Cuevas | 1 | 1 | 10 | 1 | 0.05 |
| 4846 | Michael Frank | 1 | 1 | 10 | 1 | 0.05 |
| 4847 | Michael Pearson | 1 | 1 | 10 | 1 | 0.05 |
| 4848 | Michael Williamson | 1 | 1 | 10 | 1 | 0.05 |
| 4849 | Nicholas Moss | 1 | 1 | 10 | 1 | 0.05 |
| 4850 | Rachel Rios | 1 | 1 | 10 | 1 | 0.05 |
| 4851 | Rainer Mans | 1 | 1 | 10 | 1 | 0.05 |
| 4852 | Ryan Baxter | 1 | 1 | 10 | 1 | 0.05 |
| 4853 | Sami Bohnbach | 1 | 1 | 10 | 1 | 0.05 |
| 4854 | Sarah Benson | 1 | 1 | 10 | 1 | 0.05 |
| 4855 | Sonia Porzio | 1 | 1 | 10 | 1 | 0.05 |
| 4856 | Stanley Roberts | 1 | 1 | 10 | 1 | 0.05 |
| 4857 | Tammie Johnson | 1 | 1 | 10 | 1 | 0.05 |
| 4858 | Tao Tan | 1 | 1 | 10 | 1 | 0.05 |
| 4859 | Temistocle Vivaldi-Amato | 1 | 1 | 10 | 1 | 0.05 |
| 4860 | Thomas Leon | 1 | 1 | 10 | 1 | 0.05 |
| 4861 | Todd Mcbride | 1 | 1 | 10 | 1 | 0.05 |
| 4862 | Wei Song | 1 | 1 | 10 | 1 | 0.05 |
| 4863 | Whisper Cascade | 1 | 1 | 10 | 1 | 0.05 |
| 4864 | William Vollbrecht | 1 | 1 | 10 | 1 | 0.05 |
| 4865 | Wiltrud Hübel | 1 | 1 | 10 | 1 | 0.05 |
| 4866 | Yan Mao | 1 | 1 | 10 | 1 | 0.05 |
| 4867 | Yan Pan | 1 | 1 | 10 | 1 | 0.05 |
| 4868 | Yang Shen | 1 | 1 | 10 | 1 | 0.05 |
| 4869 | Yvonne Powell | 1 | 1 | 10 | 1 | 0.05 |
| 4870 | Amanda Frazier | 1 | 1 | 6 | 2 | 0.05 |
| 4871 | Anthony Farmer | 1 | 1 | 6 | 2 | 0.05 |
| 4872 | Austin Martin | 1 | 1 | 6 | 2 | 0.05 |
| 4873 | Beverly Powell | 1 | 1 | 6 | 2 | 0.05 |
| 4874 | Cody Rowe | 1 | 1 | 6 | 2 | 0.05 |
| 4875 | Debra Anderson | 1 | 1 | 6 | 2 | 0.05 |
| 4876 | Grzegorz Rorat | 1 | 1 | 6 | 2 | 0.05 |
| 4877 | James Mcmahon | 1 | 1 | 6 | 2 | 0.05 |
| 4878 | Jeffrey Hill | 1 | 1 | 6 | 2 | 0.05 |
| 4879 | John Sanchez | 1 | 1 | 6 | 2 | 0.05 |
| 4880 | Kenichi Matsuda | 1 | 1 | 6 | 2 | 0.05 |
| 4881 | Maite Cuevas Caballero | 1 | 1 | 6 | 2 | 0.05 |
| 4882 | Milena Anichini-Barracco | 1 | 1 | 6 | 2 | 0.05 |
| 4883 | Nicolas Marsh | 1 | 1 | 6 | 2 | 0.05 |
| 4884 | Samantha Hughes | 1 | 1 | 6 | 2 | 0.05 |
| 4885 | Shannon Oneill | 1 | 1 | 6 | 2 | 0.05 |
| 4886 | Steven Medina | 1 | 1 | 6 | 2 | 0.05 |
| 4887 | Tao Wu | 1 | 1 | 6 | 2 | 0.05 |
| 4888 | Tomoya Shimizu | 1 | 1 | 6 | 2 | 0.05 |
| 4889 | Travis Tucker | 1 | 1 | 6 | 2 | 0.05 |
| 4890 | Tomoya Kato | 1 | 1 | 2 | 3 | 0.05 |
| 4891 | Emily Perkins | 1 | 1 | 13 | 0 | 0.05 |
| 4892 | John Johnston | 1 | 1 | 13 | 0 | 0.05 |
| 4893 | Joseph Rodriguez | 1 | 1 | 13 | 0 | 0.05 |
| 4894 | Kimberly Lee | 1 | 1 | 13 | 0 | 0.05 |
| 4895 | Kristina Serrano | 1 | 1 | 13 | 0 | 0.05 |
| 4896 | Melissa Johnson | 1 | 1 | 13 | 0 | 0.05 |
| 4897 | Amy Marshall | 1 | 1 | 9 | 1 | 0.05 |
| 4898 | Andrea Brooks | 1 | 1 | 9 | 1 | 0.05 |
| 4899 | Andrew Williamson | 1 | 1 | 9 | 1 | 0.05 |
| 4900 | Anka Spieß | 1 | 1 | 9 | 1 | 0.05 |
| 4901 | Anthony Garcia | 1 | 1 | 9 | 1 | 0.05 |
| 4902 | Ashley Jennings | 1 | 1 | 9 | 1 | 0.05 |
| 4903 | Bianka Herrmann | 1 | 1 | 9 | 1 | 0.05 |
| 4904 | Brent Larsen | 1 | 1 | 9 | 1 | 0.05 |
| 4905 | Brian Morales | 1 | 1 | 9 | 1 | 0.05 |
| 4906 | Brooke Ortiz | 1 | 1 | 9 | 1 | 0.05 |
| 4907 | Carlos Mccann | 1 | 1 | 9 | 1 | 0.05 |
| 4908 | Casey Price | 1 | 1 | 9 | 1 | 0.05 |
| 4909 | Catherine Price | 1 | 1 | 9 | 1 | 0.05 |
| 4910 | Chelsea Paul | 1 | 1 | 9 | 1 | 0.05 |
| 4911 | Cheryl Brown | 1 | 1 | 9 | 1 | 0.05 |
| 4912 | Chiyo Suzuki | 1 | 1 | 9 | 1 | 0.05 |
| 4913 | Christine Jennings | 1 | 1 | 9 | 1 | 0.05 |
| 4914 | Christopher Cox | 1 | 1 | 9 | 1 | 0.05 |
| 4915 | Christopher Miller | 1 | 1 | 9 | 1 | 0.05 |
| 4916 | Christopher Wilson | 1 | 1 | 9 | 1 | 0.05 |
| 4917 | Cody Lopez | 1 | 1 | 9 | 1 | 0.05 |
| 4918 | Courtney Smith | 1 | 1 | 9 | 1 | 0.05 |
| 4919 | Crystal Yu | 1 | 1 | 9 | 1 | 0.05 |
| 4920 | Danielle Franklin | 1 | 1 | 9 | 1 | 0.05 |
| 4921 | Dennis Fields | 1 | 1 | 9 | 1 | 0.05 |
| 4922 | Donald Oliver | 1 | 1 | 9 | 1 | 0.05 |
| 4923 | Edward Matthews | 1 | 1 | 9 | 1 | 0.05 |
| 4924 | Elena Nibali | 1 | 1 | 9 | 1 | 0.05 |
| 4925 | Elenore Wulff | 1 | 1 | 9 | 1 | 0.05 |
| 4926 | Erica Hill | 1 | 1 | 9 | 1 | 0.05 |
| 4927 | Erika Martin | 1 | 1 | 9 | 1 | 0.05 |
| 4928 | Fabian Durys | 1 | 1 | 9 | 1 | 0.05 |
| 4929 | Fabienne Klemm-Kade | 1 | 1 | 9 | 1 | 0.05 |
| 4930 | Fang Fan | 1 | 1 | 9 | 1 | 0.05 |
| 4931 | Fang Zhang | 1 | 1 | 9 | 1 | 0.05 |
| 4932 | Frank Osborne | 1 | 1 | 9 | 1 | 0.05 |
| 4933 | Gioffre Garobbio | 1 | 1 | 9 | 1 | 0.05 |
| 4934 | Holly Horton | 1 | 1 | 9 | 1 | 0.05 |
| 4935 | Hubertine Plath | 1 | 1 | 9 | 1 | 0.05 |
| 4936 | Ida Burzec | 1 | 1 | 9 | 1 | 0.05 |
| 4937 | Irmtraut Benthin | 1 | 1 | 9 | 1 | 0.05 |
| 4938 | Jaclyn Smith | 1 | 1 | 9 | 1 | 0.05 |
| 4939 | James Bishop | 1 | 1 | 9 | 1 | 0.05 |
| 4940 | Janice Poole | 1 | 1 | 9 | 1 | 0.05 |
| 4941 | Jing Liu | 1 | 1 | 9 | 1 | 0.05 |
| 4942 | Jose Brown | 1 | 1 | 9 | 1 | 0.05 |
| 4943 | Joshua Shelton | 1 | 1 | 9 | 1 | 0.05 |
| 4944 | Juergen Carsten | 1 | 1 | 9 | 1 | 0.05 |
| 4945 | Justin Hensley | 1 | 1 | 9 | 1 | 0.05 |
| 4946 | Justin Powers | 1 | 1 | 9 | 1 | 0.05 |
| 4947 | Kana Mori | 1 | 1 | 9 | 1 | 0.05 |
| 4948 | Kaori Watanabe | 1 | 1 | 9 | 1 | 0.05 |
| 4949 | Karen Robinson | 1 | 1 | 9 | 1 | 0.05 |
| 4950 | Kathryn Smith | 1 | 1 | 9 | 1 | 0.05 |
| 4951 | Kenneth Evans | 1 | 1 | 9 | 1 | 0.05 |
| 4952 | Kristen Hamilton | 1 | 1 | 9 | 1 | 0.05 |
| 4953 | Kristen Porter | 1 | 1 | 9 | 1 | 0.05 |
| 4954 | Laura Harrison | 1 | 1 | 9 | 1 | 0.05 |
| 4955 | Lauren Mclean | 1 | 1 | 9 | 1 | 0.05 |
| 4956 | Leah Dixon | 1 | 1 | 9 | 1 | 0.05 |
| 4957 | Li Qin | 1 | 1 | 9 | 1 | 0.05 |
| 4958 | Magdalene Fliegner | 1 | 1 | 9 | 1 | 0.05 |
| 4959 | Manuel Wu | 1 | 1 | 9 | 1 | 0.05 |
| 4960 | Mark Heath | 1 | 1 | 9 | 1 | 0.05 |
| 4961 | Matthew Chapman | 1 | 1 | 9 | 1 | 0.05 |
| 4962 | Maurice Nguyen | 1 | 1 | 9 | 1 | 0.05 |
| 4963 | Melissa Avila | 1 | 1 | 9 | 1 | 0.05 |
| 4964 | Ming Dong | 1 | 1 | 9 | 1 | 0.05 |
| 4965 | Ming Yi | 1 | 1 | 9 | 1 | 0.05 |
| 4966 | Mitchell Larson | 1 | 1 | 9 | 1 | 0.05 |
| 4967 | Nadia Mazzanti | 1 | 1 | 9 | 1 | 0.05 |
| 4968 | Nicholas Bond | 1 | 1 | 9 | 1 | 0.05 |
| 4969 | Nicholas Lawrence | 1 | 1 | 9 | 1 | 0.05 |
| 4970 | Olivia Clark | 1 | 1 | 9 | 1 | 0.05 |
| 4971 | Peter Banks | 1 | 1 | 9 | 1 | 0.05 |
| 4972 | Rebecca Wheeler | 1 | 1 | 9 | 1 | 0.05 |
| 4973 | Renata Manolesso | 1 | 1 | 9 | 1 | 0.05 |
| 4974 | Robert Gonzalez | 1 | 1 | 9 | 1 | 0.05 |
| 4975 | Rudi Bolander-Zimmer | 1 | 1 | 9 | 1 | 0.05 |
| 4976 | Ryan Johnston | 1 | 1 | 9 | 1 | 0.05 |
| 4977 | Scott Kennedy | 1 | 1 | 9 | 1 | 0.05 |
| 4978 | Sophia Zaguri | 1 | 1 | 9 | 1 | 0.05 |
| 4979 | Stacey Bruce | 1 | 1 | 9 | 1 | 0.05 |
| 4980 | Stephen Thompson | 1 | 1 | 9 | 1 | 0.05 |
| 4981 | Summer Friedman | 1 | 1 | 9 | 1 | 0.05 |
| 4982 | Susan Stewart | 1 | 1 | 9 | 1 | 0.05 |
| 4983 | Sylvia Lawrence | 1 | 1 | 9 | 1 | 0.05 |
| 4984 | Taichi Sasaki | 1 | 1 | 9 | 1 | 0.05 |
| 4985 | Terry Harris | 1 | 1 | 9 | 1 | 0.05 |
| 4986 | Thomas Lopez | 1 | 1 | 9 | 1 | 0.05 |
| 4987 | Tim Johnson | 1 | 1 | 9 | 1 | 0.05 |
| 4988 | Tola Cymer | 1 | 1 | 9 | 1 | 0.05 |
| 4989 | Tomoya Nakamura | 1 | 1 | 9 | 1 | 0.05 |
| 4990 | Tomoya Takahashi | 1 | 1 | 9 | 1 | 0.05 |
| 4991 | Urszula Henke | 1 | 1 | 9 | 1 | 0.05 |
| 4992 | Wei Chen | 1 | 1 | 9 | 1 | 0.05 |
| 4993 | Wojciech Jarmuła | 1 | 1 | 9 | 1 | 0.05 |
| 4994 | Xiulan Bai | 1 | 1 | 9 | 1 | 0.05 |
| 4995 | Yan Dong | 1 | 1 | 9 | 1 | 0.05 |
| 4996 | Yong Cheng | 1 | 1 | 9 | 1 | 0.05 |
| 4997 | Yong Kang | 1 | 1 | 9 | 1 | 0.05 |
| 4998 | Yong Luo | 1 | 1 | 9 | 1 | 0.05 |
| 4999 | Yuki Hashimoto | 1 | 1 | 9 | 1 | 0.05 |
| 5000 | Olga Kalinka | 1 | 0 | 15 | 4 | 0.05 |
| 5001 | Adira Ramaswamy | 1 | 1 | 5 | 2 | 0.05 |
| 5002 | Catherine Bolton | 1 | 1 | 5 | 2 | 0.05 |
| 5003 | Christina Villa | 1 | 1 | 5 | 2 | 0.05 |
| 5004 | Christine Hauffer | 1 | 1 | 5 | 2 | 0.05 |
| 5005 | Daniela Scholtz | 1 | 1 | 5 | 2 | 0.05 |
| 5006 | Drishya Setty | 1 | 1 | 5 | 2 | 0.05 |
| 5007 | Jennifer Alvarez | 1 | 1 | 5 | 2 | 0.05 |
| 5008 | Jonathan Adams | 1 | 1 | 5 | 2 | 0.05 |
| 5009 | Kristen Edwards | 1 | 1 | 5 | 2 | 0.05 |
| 5010 | Laurent-Léon Morvan | 1 | 1 | 5 | 2 | 0.05 |
| 5011 | Lori Massey | 1 | 1 | 5 | 2 | 0.05 |
| 5012 | Lucie Tanguy | 1 | 1 | 5 | 2 | 0.05 |
| 5013 | Patrick Banks | 1 | 1 | 5 | 2 | 0.05 |
| 5014 | Philippe Carre de la Humbert | 1 | 1 | 5 | 2 | 0.05 |
| 5015 | Randy Stewart | 1 | 1 | 5 | 2 | 0.05 |
| 5016 | Ronald Ramirez | 1 | 1 | 5 | 2 | 0.05 |
| 5017 | Samar Dutta | 1 | 1 | 5 | 2 | 0.05 |
| 5018 | Sarah Patrick | 1 | 1 | 5 | 2 | 0.05 |
| 5019 | Subterranean Whispers | 1 | 1 | 5 | 2 | 0.05 |
| 5020 | William White | 1 | 1 | 5 | 2 | 0.05 |
| 5021 | Adam Smith | 1 | 1 | 12 | 0 | 0.05 |
| 5022 | Adrian Ross | 1 | 1 | 12 | 0 | 0.05 |
| 5023 | Alexander Rose | 1 | 1 | 12 | 0 | 0.05 |
| 5024 | Audrey Fritz | 1 | 1 | 12 | 0 | 0.05 |
| 5025 | Bartek Heleniak | 1 | 1 | 12 | 0 | 0.05 |
| 5026 | Christopher Fischer | 1 | 1 | 12 | 0 | 0.05 |
| 5027 | Craig Villanueva | 1 | 1 | 12 | 0 | 0.05 |
| 5028 | David Robinson | 1 | 1 | 12 | 0 | 0.05 |
| 5029 | Denny Scholl-Vogt | 1 | 1 | 12 | 0 | 0.05 |
| 5030 | Dominique Newton | 1 | 1 | 12 | 0 | 0.05 |
| 5031 | Dylan Miller | 1 | 1 | 12 | 0 | 0.05 |
| 5032 | Elaine Miller | 1 | 1 | 12 | 0 | 0.05 |
| 5033 | Felizitas Hermann | 1 | 1 | 12 | 0 | 0.05 |
| 5034 | Jerzy Majczyna | 1 | 1 | 12 | 0 | 0.05 |
| 5035 | Jonathan Gonzales | 1 | 1 | 12 | 0 | 0.05 |
| 5036 | Karen Rodriguez | 1 | 1 | 12 | 0 | 0.05 |
| 5037 | Mackenzie Garza | 1 | 1 | 12 | 0 | 0.05 |
| 5038 | Magret Staude | 1 | 1 | 12 | 0 | 0.05 |
| 5039 | Patricia Maynard | 1 | 1 | 12 | 0 | 0.05 |
| 5040 | Paul Hale | 1 | 1 | 12 | 0 | 0.05 |
| 5041 | Rebecca Bennett | 1 | 1 | 12 | 0 | 0.05 |
| 5042 | Regina Yang | 1 | 1 | 12 | 0 | 0.05 |
| 5043 | Rhonda Mendez | 1 | 1 | 12 | 0 | 0.05 |
| 5044 | Sara Chung | 1 | 1 | 12 | 0 | 0.05 |
| 5045 | Sonia Trochimiuk | 1 | 1 | 12 | 0 | 0.05 |
| 5046 | Summer Diaz | 1 | 1 | 12 | 0 | 0.05 |
| 5047 | Thomas Robinson | 1 | 1 | 12 | 0 | 0.05 |
| 5048 | Xiulan Qian | 1 | 1 | 12 | 0 | 0.05 |
| 5049 | Alexander Ramirez | 1 | 1 | 8 | 1 | 0.05 |
| 5050 | Amanda Boitani | 1 | 1 | 8 | 1 | 0.05 |
| 5051 | Amanda Lee | 1 | 1 | 8 | 1 | 0.05 |
| 5052 | Amy Frazier | 1 | 1 | 8 | 1 | 0.05 |
| 5053 | Anastazja Siedlik | 1 | 1 | 8 | 1 | 0.05 |
| 5054 | Andrew Gordon | 1 | 1 | 8 | 1 | 0.05 |
| 5055 | Anna Coleman | 1 | 1 | 8 | 1 | 0.05 |
| 5056 | Annetta Dallapé | 1 | 1 | 8 | 1 | 0.05 |
| 5057 | Anthony Navarro | 1 | 1 | 8 | 1 | 0.05 |
| 5058 | Baptist Adolph | 1 | 1 | 8 | 1 | 0.05 |
| 5059 | Beverly Lloyd | 1 | 1 | 8 | 1 | 0.05 |
| 5060 | Bobby Ruiz | 1 | 1 | 8 | 1 | 0.05 |
| 5061 | Bradley Mendez | 1 | 1 | 8 | 1 | 0.05 |
| 5062 | Breanna Neal | 1 | 1 | 8 | 1 | 0.05 |
| 5063 | Calcedonio Abbagnale | 1 | 1 | 8 | 1 | 0.05 |
| 5064 | Carrie Lang | 1 | 1 | 8 | 1 | 0.05 |
| 5065 | Carrie Pace | 1 | 1 | 8 | 1 | 0.05 |
| 5066 | Cesar Mcpherson | 1 | 1 | 8 | 1 | 0.05 |
| 5067 | Chao Feng | 1 | 1 | 8 | 1 | 0.05 |
| 5068 | Crystal Caldwell | 1 | 1 | 8 | 1 | 0.05 |
| 5069 | Dana Griffin | 1 | 1 | 8 | 1 | 0.05 |
| 5070 | Darlene Chase | 1 | 1 | 8 | 1 | 0.05 |
| 5071 | David Higgins | 1 | 1 | 8 | 1 | 0.05 |
| 5072 | Dean Mullins | 1 | 1 | 8 | 1 | 0.05 |
| 5073 | Deborah Odonnell | 1 | 1 | 8 | 1 | 0.05 |
| 5074 | Diana Johnson | 1 | 1 | 8 | 1 | 0.05 |
| 5075 | Eduardo Gonzalez | 1 | 1 | 8 | 1 | 0.05 |
| 5076 | Elizabeth Evans | 1 | 1 | 8 | 1 | 0.05 |
| 5077 | Elizabeth Martin | 1 | 1 | 8 | 1 | 0.05 |
| 5078 | Federico Offredi | 1 | 1 | 8 | 1 | 0.05 |
| 5079 | Guido Sbarbaro | 1 | 1 | 8 | 1 | 0.05 |
| 5080 | Guiying Xiong | 1 | 1 | 8 | 1 | 0.05 |
| 5081 | Haley Williams | 1 | 1 | 8 | 1 | 0.05 |
| 5082 | Heer Balan | 1 | 1 | 8 | 1 | 0.05 |
| 5083 | Heinz-Günter Kallert | 1 | 1 | 8 | 1 | 0.05 |
| 5084 | Ishaan Mahal | 1 | 1 | 8 | 1 | 0.05 |
| 5085 | James Gibson | 1 | 1 | 8 | 1 | 0.05 |
| 5086 | Jamie Davis | 1 | 1 | 8 | 1 | 0.05 |
| 5087 | Jie Kong | 1 | 1 | 8 | 1 | 0.05 |
| 5088 | Joel Collins | 1 | 1 | 8 | 1 | 0.05 |
| 5089 | Joseph Brooks | 1 | 1 | 8 | 1 | 0.05 |
| 5090 | Joyce Jackson | 1 | 1 | 8 | 1 | 0.05 |
| 5091 | Jun Ma | 1 | 1 | 8 | 1 | 0.05 |
| 5092 | Justin Morse | 1 | 1 | 8 | 1 | 0.05 |
| 5093 | Kajetan Ryszkiewicz | 1 | 1 | 8 | 1 | 0.05 |
| 5094 | Karen Garcia | 1 | 1 | 8 | 1 | 0.05 |
| 5095 | Katherine Watts | 1 | 1 | 8 | 1 | 0.05 |
| 5096 | Katrina Valentine | 1 | 1 | 8 | 1 | 0.05 |
| 5097 | Kristen Rice | 1 | 1 | 8 | 1 | 0.05 |
| 5098 | Kyle Daniel | 1 | 1 | 8 | 1 | 0.05 |
| 5099 | Laura Roberts | 1 | 1 | 8 | 1 | 0.05 |
| 5100 | Laura Sloan | 1 | 1 | 8 | 1 | 0.05 |
| 5101 | Leah Robinson | 1 | 1 | 8 | 1 | 0.05 |
| 5102 | Lei Xia | 1 | 1 | 8 | 1 | 0.05 |
| 5103 | Liwia Głuszko | 1 | 1 | 8 | 1 | 0.05 |
| 5104 | Lorenzo Orengo | 1 | 1 | 8 | 1 | 0.05 |
| 5105 | Madison Lopez | 1 | 1 | 8 | 1 | 0.05 |
| 5106 | Maria Fletcher | 1 | 1 | 8 | 1 | 0.05 |
| 5107 | Maria-Luise Klemm | 1 | 1 | 8 | 1 | 0.05 |
| 5108 | Mary Gomez | 1 | 1 | 8 | 1 | 0.05 |
| 5109 | Matthew Caldwell | 1 | 1 | 8 | 1 | 0.05 |
| 5110 | Matthew Gibson | 1 | 1 | 8 | 1 | 0.05 |
| 5111 | Matthew Li | 1 | 1 | 8 | 1 | 0.05 |
| 5112 | Matthew Roberson | 1 | 1 | 8 | 1 | 0.05 |
| 5113 | Michael Ramirez | 1 | 1 | 8 | 1 | 0.05 |
| 5114 | Mieszko Dorna | 1 | 1 | 8 | 1 | 0.05 |
| 5115 | Nadja Gnatz | 1 | 1 | 8 | 1 | 0.05 |
| 5116 | Nino Carfagna-Totino | 1 | 1 | 8 | 1 | 0.05 |
| 5117 | Oskar Radzewicz | 1 | 1 | 8 | 1 | 0.05 |
| 5118 | Patrick Davenport | 1 | 1 | 8 | 1 | 0.05 |
| 5119 | Paul Burns | 1 | 1 | 8 | 1 | 0.05 |
| 5120 | Robert Lopez | 1 | 1 | 8 | 1 | 0.05 |
| 5121 | Roger Allen | 1 | 1 | 8 | 1 | 0.05 |
| 5122 | Ruy Villa Coloma | 1 | 1 | 8 | 1 | 0.05 |
| 5123 | Ryan Bailey | 1 | 1 | 8 | 1 | 0.05 |
| 5124 | Samantha Walters | 1 | 1 | 8 | 1 | 0.05 |
| 5125 | Sara Hołubowicz | 1 | 1 | 8 | 1 | 0.05 |
| 5126 | Sean Aguirre | 1 | 1 | 8 | 1 | 0.05 |
| 5127 | Tammy Washington | 1 | 1 | 8 | 1 | 0.05 |
| 5128 | Tao Xiao | 1 | 1 | 8 | 1 | 0.05 |
| 5129 | Terry Castillo | 1 | 1 | 8 | 1 | 0.05 |
| 5130 | Thomas Stephens | 1 | 1 | 8 | 1 | 0.05 |
| 5131 | Tiffany Mckee | 1 | 1 | 8 | 1 | 0.05 |
| 5132 | Todd Reed | 1 | 1 | 8 | 1 | 0.05 |
| 5133 | Valerie Stafford | 1 | 1 | 8 | 1 | 0.05 |
| 5134 | Wendy Flores | 1 | 1 | 8 | 1 | 0.05 |
| 5135 | Wiktor Kazimierczyk | 1 | 1 | 8 | 1 | 0.05 |
| 5136 | William Hawkins | 1 | 1 | 8 | 1 | 0.05 |
| 5137 | William Lynch | 1 | 1 | 8 | 1 | 0.05 |
| 5138 | Xia He | 1 | 1 | 8 | 1 | 0.05 |
| 5139 | Yong Li | 1 | 1 | 8 | 1 | 0.05 |
| 5140 | Yuvaan Chopra | 1 | 1 | 8 | 1 | 0.05 |
| 5141 | Amy Ochoa | 1 | 1 | 4 | 2 | 0.05 |
| 5142 | Calvin Kemp | 1 | 1 | 4 | 2 | 0.05 |
| 5143 | Erica Padilla | 1 | 1 | 4 | 2 | 0.05 |
| 5144 | Jason Lopez | 1 | 1 | 4 | 2 | 0.05 |
| 5145 | Juanita Galván | 1 | 1 | 4 | 2 | 0.05 |
| 5146 | Julia Smith | 1 | 1 | 4 | 2 | 0.05 |
| 5147 | Khushi Upadhyay | 1 | 1 | 4 | 2 | 0.05 |
| 5148 | Kumiko Fujita | 1 | 1 | 4 | 2 | 0.05 |
| 5149 | Maaya Tanaka | 1 | 1 | 4 | 2 | 0.05 |
| 5150 | Marcel Kutek | 1 | 1 | 4 | 2 | 0.05 |
| 5151 | Matthew Garcia | 1 | 1 | 4 | 2 | 0.05 |
| 5152 | Patrick Carney | 1 | 1 | 4 | 2 | 0.05 |
| 5153 | Paula Palmer | 1 | 1 | 4 | 2 | 0.05 |
| 5154 | William Rojas | 1 | 1 | 4 | 2 | 0.05 |
| 5155 | Yuta Sato | 1 | 1 | 4 | 2 | 0.05 |
| 5156 | Alex Mathis | 1 | 1 | 11 | 0 | 0.05 |
| 5157 | Allen Smith | 1 | 1 | 11 | 0 | 0.05 |
| 5158 | Amy Ramos | 1 | 1 | 11 | 0 | 0.05 |
| 5159 | Amy Wood | 1 | 1 | 11 | 0 | 0.05 |
| 5160 | Brenda Day | 1 | 1 | 11 | 0 | 0.05 |
| 5161 | Chelsea Young | 1 | 1 | 11 | 0 | 0.05 |
| 5162 | Christopher Nelson | 1 | 1 | 11 | 0 | 0.05 |
| 5163 | Dana Patterson | 1 | 1 | 11 | 0 | 0.05 |
| 5164 | Edward Dixon | 1 | 1 | 11 | 0 | 0.05 |
| 5165 | Edward Hamilton | 1 | 1 | 11 | 0 | 0.05 |
| 5166 | Ellen Bradley | 1 | 1 | 11 | 0 | 0.05 |
| 5167 | Garrett Dixon | 1 | 1 | 11 | 0 | 0.05 |
| 5168 | Jasmine Nichols | 1 | 1 | 11 | 0 | 0.05 |
| 5169 | Jason Stevens | 1 | 1 | 11 | 0 | 0.05 |
| 5170 | Jessica Brown | 1 | 1 | 11 | 0 | 0.05 |
| 5171 | Jose Morse | 1 | 1 | 11 | 0 | 0.05 |
| 5172 | Joshua Mckenzie | 1 | 1 | 11 | 0 | 0.05 |
| 5173 | Juan Tian | 1 | 1 | 11 | 0 | 0.05 |
| 5174 | Kelly Kim | 1 | 1 | 11 | 0 | 0.05 |
| 5175 | Kristen Carlson | 1 | 1 | 11 | 0 | 0.05 |
| 5176 | Leah Thomas | 1 | 1 | 11 | 0 | 0.05 |
| 5177 | Lisa Wright | 1 | 1 | 11 | 0 | 0.05 |
| 5178 | Luis Green | 1 | 1 | 11 | 0 | 0.05 |
| 5179 | Megan Diaz | 1 | 1 | 11 | 0 | 0.05 |
| 5180 | Nicole Hodges | 1 | 1 | 11 | 0 | 0.05 |
| 5181 | Ryan Carter | 1 | 1 | 11 | 0 | 0.05 |
| 5182 | Stephen Davis | 1 | 1 | 11 | 0 | 0.05 |
| 5183 | Timothy Watson | 1 | 1 | 11 | 0 | 0.05 |
| 5184 | Willie Johnson | 1 | 1 | 11 | 0 | 0.05 |
| 5185 | Yong Fang | 1 | 1 | 11 | 0 | 0.05 |
| 5186 | Alexander Rivera | 1 | 1 | 7 | 1 | 0.05 |
| 5187 | Alfredo Roth | 1 | 1 | 7 | 1 | 0.05 |
| 5188 | Allison Duran | 1 | 1 | 7 | 1 | 0.05 |
| 5189 | Amanda Ramos | 1 | 1 | 7 | 1 | 0.05 |
| 5190 | Amy Coleman | 1 | 1 | 7 | 1 | 0.05 |
| 5191 | Amy Gutierrez | 1 | 1 | 7 | 1 | 0.05 |
| 5192 | Andrea Obrien | 1 | 1 | 7 | 1 | 0.05 |
| 5193 | Ann Petersen | 1 | 1 | 7 | 1 | 0.05 |
| 5194 | Antonia Farinelli | 1 | 1 | 7 | 1 | 0.05 |
| 5195 | Antonia Mülichen | 1 | 1 | 7 | 1 | 0.05 |
| 5196 | Brandon Mccormick | 1 | 1 | 7 | 1 | 0.05 |
| 5197 | Brandon Payne | 1 | 1 | 7 | 1 | 0.05 |
| 5198 | Brian Perez | 1 | 1 | 7 | 1 | 0.05 |
| 5199 | Brian Ramos | 1 | 1 | 7 | 1 | 0.05 |
| 5200 | Bryan Sandoval | 1 | 1 | 7 | 1 | 0.05 |
| 5201 | Carl Rush | 1 | 1 | 7 | 1 | 0.05 |
| 5202 | Chao Huang | 1 | 1 | 7 | 1 | 0.05 |
| 5203 | Christian Rojas | 1 | 1 | 7 | 1 | 0.05 |
| 5204 | Ciro Campano | 1 | 1 | 7 | 1 | 0.05 |
| 5205 | Claudius Geißler | 1 | 1 | 7 | 1 | 0.05 |
| 5206 | Cynthia Robbins | 1 | 1 | 7 | 1 | 0.05 |
| 5207 | Dana Martin | 1 | 1 | 7 | 1 | 0.05 |
| 5208 | Daniel Aubry | 1 | 1 | 7 | 1 | 0.05 |
| 5209 | Daryl Parsons | 1 | 1 | 7 | 1 | 0.05 |
| 5210 | David Bowen | 1 | 1 | 7 | 1 | 0.05 |
| 5211 | Deborah Davis | 1 | 1 | 7 | 1 | 0.05 |
| 5212 | Debra Lam | 1 | 1 | 7 | 1 | 0.05 |
| 5213 | Derek Carpenter | 1 | 1 | 7 | 1 | 0.05 |
| 5214 | Dionigi Granatelli | 1 | 1 | 7 | 1 | 0.05 |
| 5215 | Donna Bennett | 1 | 1 | 7 | 1 | 0.05 |
| 5216 | Egon Wilmsen-Röhrdanz | 1 | 1 | 7 | 1 | 0.05 |
| 5217 | Elena Germano | 1 | 1 | 7 | 1 | 0.05 |
| 5218 | Elisa Zoppetti-Venturi | 1 | 1 | 7 | 1 | 0.05 |
| 5219 | Elizabeth Newton PhD | 1 | 1 | 7 | 1 | 0.05 |
| 5220 | Eugene Turner | 1 | 1 | 7 | 1 | 0.05 |
| 5221 | Florence Hermighausen | 1 | 1 | 7 | 1 | 0.05 |
| 5222 | Gabriel Seip | 1 | 1 | 7 | 1 | 0.05 |
| 5223 | Gang Gong | 1 | 1 | 7 | 1 | 0.05 |
| 5224 | Gang Song | 1 | 1 | 7 | 1 | 0.05 |
| 5225 | Greco Guarato | 1 | 1 | 7 | 1 | 0.05 |
| 5226 | Guido Conti | 1 | 1 | 7 | 1 | 0.05 |
| 5227 | Guiying Yu | 1 | 1 | 7 | 1 | 0.05 |
| 5228 | Hannes Ziegert | 1 | 1 | 7 | 1 | 0.05 |
| 5229 | Heidi Bradley | 1 | 1 | 7 | 1 | 0.05 |
| 5230 | Heidi Richardson | 1 | 1 | 7 | 1 | 0.05 |
| 5231 | Holly Riley | 1 | 1 | 7 | 1 | 0.05 |
| 5232 | Ignacy Henke | 1 | 1 | 7 | 1 | 0.05 |
| 5233 | Jacqueline Lawson | 1 | 1 | 7 | 1 | 0.05 |
| 5234 | James Dudley | 1 | 1 | 7 | 1 | 0.05 |
| 5235 | James Valentine | 1 | 1 | 7 | 1 | 0.05 |
| 5236 | Jamie Rodgers | 1 | 1 | 7 | 1 | 0.05 |
| 5237 | Jason Garcia | 1 | 1 | 7 | 1 | 0.05 |
| 5238 | Javi Fuente Benavente | 1 | 1 | 7 | 1 | 0.05 |
| 5239 | Jenny Dunn | 1 | 1 | 7 | 1 | 0.05 |
| 5240 | Jeremy Rodriguez | 1 | 1 | 7 | 1 | 0.05 |
| 5241 | Jerzy Ksel | 1 | 1 | 7 | 1 | 0.05 |
| 5242 | Jessica Bradley | 1 | 1 | 7 | 1 | 0.05 |
| 5243 | Jie Chang | 1 | 1 | 7 | 1 | 0.05 |
| 5244 | Jie Shi | 1 | 1 | 7 | 1 | 0.05 |
| 5245 | Jill Conley | 1 | 1 | 7 | 1 | 0.05 |
| 5246 | Joseph Alvarez | 1 | 1 | 7 | 1 | 0.05 |
| 5247 | Julie Mcgrath | 1 | 1 | 7 | 1 | 0.05 |
| 5248 | Julie Rowe | 1 | 1 | 7 | 1 | 0.05 |
| 5249 | Kari Dillon | 1 | 1 | 7 | 1 | 0.05 |
| 5250 | Kathy Phillips | 1 | 1 | 7 | 1 | 0.05 |
| 5251 | Kelsey Martinez | 1 | 1 | 7 | 1 | 0.05 |
| 5252 | Kenneth Moore | 1 | 1 | 7 | 1 | 0.05 |
| 5253 | Kent Chen | 1 | 1 | 7 | 1 | 0.05 |
| 5254 | Konstanty Drobek | 1 | 1 | 7 | 1 | 0.05 |
| 5255 | Li Xiang | 1 | 1 | 7 | 1 | 0.05 |
| 5256 | Lilla Giammusso | 1 | 1 | 7 | 1 | 0.05 |
| 5257 | Marcin Bernatek | 1 | 1 | 7 | 1 | 0.05 |
| 5258 | Marina Boucsein | 1 | 1 | 7 | 1 | 0.05 |
| 5259 | Marissa Evans | 1 | 1 | 7 | 1 | 0.05 |
| 5260 | Mariusz Burzec | 1 | 1 | 7 | 1 | 0.05 |
| 5261 | Mark Stein | 1 | 1 | 7 | 1 | 0.05 |
| 5262 | Matthew Crawford | 1 | 1 | 7 | 1 | 0.05 |
| 5263 | Matthew Williams | 1 | 1 | 7 | 1 | 0.05 |
| 5264 | Mattias Pohl | 1 | 1 | 7 | 1 | 0.05 |
| 5265 | Meagan Hendrix | 1 | 1 | 7 | 1 | 0.05 |
| 5266 | Megan Garcia | 1 | 1 | 7 | 1 | 0.05 |
| 5267 | Michael Buchanan | 1 | 1 | 7 | 1 | 0.05 |
| 5268 | Michael Frederick | 1 | 1 | 7 | 1 | 0.05 |
| 5269 | Mituru Matsumoto | 1 | 1 | 7 | 1 | 0.05 |
| 5270 | Na Lin | 1 | 1 | 7 | 1 | 0.05 |
| 5271 | Naoki Sato | 1 | 1 | 7 | 1 | 0.05 |
| 5272 | Nichole Moore | 1 | 1 | 7 | 1 | 0.05 |
| 5273 | Patricia Massey | 1 | 1 | 7 | 1 | 0.05 |
| 5274 | Paul Baum | 1 | 1 | 7 | 1 | 0.05 |
| 5275 | Phillip Martinez | 1 | 1 | 7 | 1 | 0.05 |
| 5276 | Ping Qiu | 1 | 1 | 7 | 1 | 0.05 |
| 5277 | Regina Davis | 1 | 1 | 7 | 1 | 0.05 |
| 5278 | Rika Maeda | 1 | 1 | 7 | 1 | 0.05 |
| 5279 | Robert Stewart | 1 | 1 | 7 | 1 | 0.05 |
| 5280 | Russell Bates | 1 | 1 | 7 | 1 | 0.05 |
| 5281 | Salvi Giorgetti | 1 | 1 | 7 | 1 | 0.05 |
| 5282 | Sarah Craig | 1 | 1 | 7 | 1 | 0.05 |
| 5283 | Sarah Harrison | 1 | 1 | 7 | 1 | 0.05 |
| 5284 | Satomi Inoue | 1 | 1 | 7 | 1 | 0.05 |
| 5285 | Sole Gagliano-Conte | 1 | 1 | 7 | 1 | 0.05 |
| 5286 | Stephanie Grant | 1 | 1 | 7 | 1 | 0.05 |
| 5287 | Suzanne Davis | 1 | 1 | 7 | 1 | 0.05 |
| 5288 | Tammy Griffin | 1 | 1 | 7 | 1 | 0.05 |
| 5289 | Taylor Pace | 1 | 1 | 7 | 1 | 0.05 |
| 5290 | Teresa Rivera | 1 | 1 | 7 | 1 | 0.05 |
| 5291 | Terrance Velazquez | 1 | 1 | 7 | 1 | 0.05 |
| 5292 | Theda Rosemann | 1 | 1 | 7 | 1 | 0.05 |
| 5293 | Thomas Miranda | 1 | 1 | 7 | 1 | 0.05 |
| 5294 | Théodore de la Chauvet | 1 | 1 | 7 | 1 | 0.05 |
| 5295 | Traci Thomas | 1 | 1 | 7 | 1 | 0.05 |
| 5296 | Wanda Smith | 1 | 1 | 7 | 1 | 0.05 |
| 5297 | Whitney Humphrey | 1 | 1 | 7 | 1 | 0.05 |
| 5298 | Whitney Torres | 1 | 1 | 7 | 1 | 0.05 |
| 5299 | William Porter | 1 | 1 | 7 | 1 | 0.05 |
| 5300 | Xia Peng | 1 | 1 | 7 | 1 | 0.05 |
| 5301 | Yan Yao | 1 | 1 | 7 | 1 | 0.05 |
| 5302 | Li Fang | 1 | 0 | 13 | 4 | 0.05 |
| 5303 | Antonia Malaparte-Leonardi | 1 | 1 | 3 | 2 | 0.05 |
| 5304 | Elizabeth Myers | 1 | 1 | 3 | 2 | 0.05 |
| 5305 | Erica Smith | 1 | 1 | 3 | 2 | 0.05 |
| 5306 | Nikol Hrubá | 1 | 1 | 3 | 2 | 0.05 |
| 5307 | Patrick Leleu | 1 | 1 | 3 | 2 | 0.05 |
| 5308 | Rosita Vollbrecht | 1 | 1 | 3 | 2 | 0.05 |
| 5309 | Rémy-Richard Devaux | 1 | 1 | 3 | 2 | 0.05 |
| 5310 | Brian Brewer | 1 | 1 | 10 | 0 | 0.05 |
| 5311 | Brittany Holmes | 1 | 1 | 10 | 0 | 0.05 |
| 5312 | Casey Farrell | 1 | 1 | 10 | 0 | 0.05 |
| 5313 | Isabell Wulff | 1 | 1 | 10 | 0 | 0.05 |
| 5314 | Jackson Monroe | 1 | 1 | 10 | 0 | 0.05 |
| 5315 | Loïs Knoers | 1 | 1 | 10 | 0 | 0.05 |
| 5316 | Megan Raymond | 1 | 1 | 10 | 0 | 0.05 |
| 5317 | Michael Bradford | 1 | 1 | 10 | 0 | 0.05 |
| 5318 | Randall Johnson | 1 | 1 | 10 | 0 | 0.05 |
| 5319 | Tao Qiu | 1 | 1 | 10 | 0 | 0.05 |
| 5320 | Abigaíl Tovar Sainz | 1 | 1 | 6 | 1 | 0.04 |
| 5321 | Adrian Miller | 1 | 1 | 6 | 1 | 0.04 |
| 5322 | Alexej Klotz | 1 | 1 | 6 | 1 | 0.04 |
| 5323 | Alfonso Albero Cervera | 1 | 1 | 6 | 1 | 0.04 |
| 5324 | Alfred Tschentscher | 1 | 1 | 6 | 1 | 0.04 |
| 5325 | Anastasio Jiménez Ferrer | 1 | 1 | 6 | 1 | 0.04 |
| 5326 | Annegret Nerger | 1 | 1 | 6 | 1 | 0.04 |
| 5327 | Ashley Brady | 1 | 1 | 6 | 1 | 0.04 |
| 5328 | Autumn Walker | 1 | 1 | 6 | 1 | 0.04 |
| 5329 | Barbara Fox | 1 | 1 | 6 | 1 | 0.04 |
| 5330 | Barry Wilkerson | 1 | 1 | 6 | 1 | 0.04 |
| 5331 | Bartek Tatarczyk | 1 | 1 | 6 | 1 | 0.04 |
| 5332 | Benoît Blanc | 1 | 1 | 6 | 1 | 0.04 |
| 5333 | Bianca Rice | 1 | 1 | 6 | 1 | 0.04 |
| 5334 | Brandon Barton | 1 | 1 | 6 | 1 | 0.04 |
| 5335 | Brett Larson | 1 | 1 | 6 | 1 | 0.04 |
| 5336 | Brian Brown | 1 | 1 | 6 | 1 | 0.04 |
| 5337 | Brian Gross | 1 | 1 | 6 | 1 | 0.04 |
| 5338 | Cassandra Washington | 1 | 1 | 6 | 1 | 0.04 |
| 5339 | Cayetana Bernal-Ocaña | 1 | 1 | 6 | 1 | 0.04 |
| 5340 | Charo Cañas Saez | 1 | 1 | 6 | 1 | 0.04 |
| 5341 | Cheryl Gibson | 1 | 1 | 6 | 1 | 0.04 |
| 5342 | Cheryl Walker | 1 | 1 | 6 | 1 | 0.04 |
| 5343 | Christopher Gutierrez | 1 | 1 | 6 | 1 | 0.04 |
| 5344 | Christopher Owens | 1 | 1 | 6 | 1 | 0.04 |
| 5345 | Christopher Whitaker | 1 | 1 | 6 | 1 | 0.04 |
| 5346 | Concepción Ripoll | 1 | 1 | 6 | 1 | 0.04 |
| 5347 | Cynthia Johns | 1 | 1 | 6 | 1 | 0.04 |
| 5348 | Damini Datta | 1 | 1 | 6 | 1 | 0.04 |
| 5349 | Debbie Fuller | 1 | 1 | 6 | 1 | 0.04 |
| 5350 | Dishani Goswami | 1 | 1 | 6 | 1 | 0.04 |
| 5351 | Divit Khanna | 1 | 1 | 6 | 1 | 0.04 |
| 5352 | Ehsaan Lall | 1 | 1 | 6 | 1 | 0.04 |
| 5353 | Elfriede Reuter | 1 | 1 | 6 | 1 | 0.04 |
| 5354 | Elsbeth Löwer | 1 | 1 | 6 | 1 | 0.04 |
| 5355 | Emelina Verdejo Otero | 1 | 1 | 6 | 1 | 0.04 |
| 5356 | Eric Shaw | 1 | 1 | 6 | 1 | 0.04 |
| 5357 | Evelína Kučerová | 1 | 1 | 6 | 1 | 0.04 |
| 5358 | Gang Meng | 1 | 1 | 6 | 1 | 0.04 |
| 5359 | Gerhart Wieloch | 1 | 1 | 6 | 1 | 0.04 |
| 5360 | Glenn Lewis | 1 | 1 | 6 | 1 | 0.04 |
| 5361 | Gloria Lewis | 1 | 1 | 6 | 1 | 0.04 |
| 5362 | Gregory Jones | 1 | 1 | 6 | 1 | 0.04 |
| 5363 | Hansh Hayer | 1 | 1 | 6 | 1 | 0.04 |
| 5364 | Herr Stephan Tschentscher | 1 | 1 | 6 | 1 | 0.04 |
| 5365 | Holly Stephens | 1 | 1 | 6 | 1 | 0.04 |
| 5366 | Ian Dorsey | 1 | 1 | 6 | 1 | 0.04 |
| 5367 | Inés del Valenciano | 1 | 1 | 6 | 1 | 0.04 |
| 5368 | Ivana Din | 1 | 1 | 6 | 1 | 0.04 |
| 5369 | Jacob Mcmahon | 1 | 1 | 6 | 1 | 0.04 |
| 5370 | Jan Hruška | 1 | 1 | 6 | 1 | 0.04 |
| 5371 | Jan Zadworny | 1 | 1 | 6 | 1 | 0.04 |
| 5372 | Jennifer Cox | 1 | 1 | 6 | 1 | 0.04 |
| 5373 | Jennifer Flores | 1 | 1 | 6 | 1 | 0.04 |
| 5374 | Jenny Rodriguez | 1 | 1 | 6 | 1 | 0.04 |
| 5375 | Jerry Ruiz | 1 | 1 | 6 | 1 | 0.04 |
| 5376 | Jessica Lucas | 1 | 1 | 6 | 1 | 0.04 |
| 5377 | Jessica Wright | 1 | 1 | 6 | 1 | 0.04 |
| 5378 | Jill Reynolds | 1 | 1 | 6 | 1 | 0.04 |
| 5379 | Jing Chen | 1 | 1 | 6 | 1 | 0.04 |
| 5380 | Jing Shao | 1 | 1 | 6 | 1 | 0.04 |
| 5381 | Jocelyn Davis | 1 | 1 | 6 | 1 | 0.04 |
| 5382 | John Brewer | 1 | 1 | 6 | 1 | 0.04 |
| 5383 | John Russo | 1 | 1 | 6 | 1 | 0.04 |
| 5384 | Johnathan Clark | 1 | 1 | 6 | 1 | 0.04 |
| 5385 | Joseph Ferguson | 1 | 1 | 6 | 1 | 0.04 |
| 5386 | Julita Łuszczak | 1 | 1 | 6 | 1 | 0.04 |
| 5387 | Karol Indyk | 1 | 1 | 6 | 1 | 0.04 |
| 5388 | Katherine Preston | 1 | 1 | 6 | 1 | 0.04 |
| 5389 | Katie Anderson | 1 | 1 | 6 | 1 | 0.04 |
| 5390 | Kelly Gilbert | 1 | 1 | 6 | 1 | 0.04 |
| 5391 | Kelly Reyes | 1 | 1 | 6 | 1 | 0.04 |
| 5392 | Kelly Williams | 1 | 1 | 6 | 1 | 0.04 |
| 5393 | Kim Preston | 1 | 1 | 6 | 1 | 0.04 |
| 5394 | Kimberly Cain | 1 | 1 | 6 | 1 | 0.04 |
| 5395 | Kornel Troka | 1 | 1 | 6 | 1 | 0.04 |
| 5396 | Lagan Bhalla | 1 | 1 | 6 | 1 | 0.04 |
| 5397 | Leif Bien | 1 | 1 | 6 | 1 | 0.04 |
| 5398 | Leslie Flynn | 1 | 1 | 6 | 1 | 0.04 |
| 5399 | Lisa Brooks | 1 | 1 | 6 | 1 | 0.04 |
| 5400 | Lorenz Förster-Barth | 1 | 1 | 6 | 1 | 0.04 |
| 5401 | Lukáš Strnad | 1 | 1 | 6 | 1 | 0.04 |
| 5402 | Malwina Kaźmierczyk | 1 | 1 | 6 | 1 | 0.04 |
| 5403 | Mannat Chopra | 1 | 1 | 6 | 1 | 0.04 |
| 5404 | Margaretha Sager | 1 | 1 | 6 | 1 | 0.04 |
| 5405 | Mary Powers | 1 | 1 | 6 | 1 | 0.04 |
| 5406 | Meredith Hamilton | 1 | 1 | 6 | 1 | 0.04 |
| 5407 | Michael Dickerson | 1 | 1 | 6 | 1 | 0.04 |
| 5408 | Michelle Eaton | 1 | 1 | 6 | 1 | 0.04 |
| 5409 | Miloslava Nováková | 1 | 1 | 6 | 1 | 0.04 |
| 5410 | Ming Gong | 1 | 1 | 6 | 1 | 0.04 |
| 5411 | Ming Lu | 1 | 1 | 6 | 1 | 0.04 |
| 5412 | Mitchell Flowers | 1 | 1 | 6 | 1 | 0.04 |
| 5413 | Mitchell Mcpherson | 1 | 1 | 6 | 1 | 0.04 |
| 5414 | Momoko Tanaka | 1 | 1 | 6 | 1 | 0.04 |
| 5415 | Nakul Samra | 1 | 1 | 6 | 1 | 0.04 |
| 5416 | Nanami Takahashi | 1 | 1 | 6 | 1 | 0.04 |
| 5417 | Nehmat Chaudhary | 1 | 1 | 6 | 1 | 0.04 |
| 5418 | Nicole Yoder | 1 | 1 | 6 | 1 | 0.04 |
| 5419 | Nitara Biswas | 1 | 1 | 6 | 1 | 0.04 |
| 5420 | Noah Braun | 1 | 1 | 6 | 1 | 0.04 |
| 5421 | Pari Chand | 1 | 1 | 6 | 1 | 0.04 |
| 5422 | Paul Harrell | 1 | 1 | 6 | 1 | 0.04 |
| 5423 | Ping Hu | 1 | 1 | 6 | 1 | 0.04 |
| 5424 | Ping Zheng | 1 | 1 | 6 | 1 | 0.04 |
| 5425 | Prerak Majumdar | 1 | 1 | 6 | 1 | 0.04 |
| 5426 | René Sans | 1 | 1 | 6 | 1 | 0.04 |
| 5427 | Richard Smith | 1 | 1 | 6 | 1 | 0.04 |
| 5428 | Rick Franklin | 1 | 1 | 6 | 1 | 0.04 |
| 5429 | Robert Fronia | 1 | 1 | 6 | 1 | 0.04 |
| 5430 | Robert Roberts | 1 | 1 | 6 | 1 | 0.04 |
| 5431 | Roman Švec | 1 | 1 | 6 | 1 | 0.04 |
| 5432 | Russell Barnes | 1 | 1 | 6 | 1 | 0.04 |
| 5433 | Sahil Tripathi | 1 | 1 | 6 | 1 | 0.04 |
| 5434 | Sarah Galloway | 1 | 1 | 6 | 1 | 0.04 |
| 5435 | Shari Willis | 1 | 1 | 6 | 1 | 0.04 |
| 5436 | Shelby Grimes | 1 | 1 | 6 | 1 | 0.04 |
| 5437 | Sophie Lebrun | 1 | 1 | 6 | 1 | 0.04 |
| 5438 | Stefan Zirme | 1 | 1 | 6 | 1 | 0.04 |
| 5439 | Steve Guzman | 1 | 1 | 6 | 1 | 0.04 |
| 5440 | Steven Schultz | 1 | 1 | 6 | 1 | 0.04 |
| 5441 | Szymon Pazik | 1 | 1 | 6 | 1 | 0.04 |
| 5442 | Tadeusz Gemza | 1 | 1 | 6 | 1 | 0.04 |
| 5443 | Terri Preston | 1 | 1 | 6 | 1 | 0.04 |
| 5444 | Theresa Mason | 1 | 1 | 6 | 1 | 0.04 |
| 5445 | Timothy Hansen | 1 | 1 | 6 | 1 | 0.04 |
| 5446 | Tracy Burton | 1 | 1 | 6 | 1 | 0.04 |
| 5447 | Tracy Ibarra | 1 | 1 | 6 | 1 | 0.04 |
| 5448 | Tracy Simpson | 1 | 1 | 6 | 1 | 0.04 |
| 5449 | Trevor Weiss | 1 | 1 | 6 | 1 | 0.04 |
| 5450 | Tyler Padilla | 1 | 1 | 6 | 1 | 0.04 |
| 5451 | Victor Spencer | 1 | 1 | 6 | 1 | 0.04 |
| 5452 | Victoria Johnson | 1 | 1 | 6 | 1 | 0.04 |
| 5453 | Viktor Švec | 1 | 1 | 6 | 1 | 0.04 |
| 5454 | Wigbert Scholl | 1 | 1 | 6 | 1 | 0.04 |
| 5455 | William Mcbride | 1 | 1 | 6 | 1 | 0.04 |
| 5456 | Xia Hou | 1 | 1 | 6 | 1 | 0.04 |
| 5457 | Yong Xie | 1 | 1 | 6 | 1 | 0.04 |
| 5458 | Yosuke Matsumoto | 1 | 1 | 6 | 1 | 0.04 |
| 5459 | Yui Watanabe | 1 | 1 | 6 | 1 | 0.04 |
| 5460 | Zara Anand | 1 | 1 | 6 | 1 | 0.04 |
| 5461 | Štěpánka Bártová | 1 | 1 | 6 | 1 | 0.04 |
| 5462 | Jeanne Perrin | 1 | 1 | 2 | 2 | 0.04 |
| 5463 | Marguerite Faure | 1 | 1 | 2 | 2 | 0.04 |
| 5464 | Alicia Kelly | 1 | 1 | 9 | 0 | 0.04 |
| 5465 | Brenda Stark | 1 | 1 | 9 | 0 | 0.04 |
| 5466 | Brittany Strickland | 1 | 1 | 9 | 0 | 0.04 |
| 5467 | Colleen Palmer | 1 | 1 | 9 | 0 | 0.04 |
| 5468 | Connie Estrada | 1 | 1 | 9 | 0 | 0.04 |
| 5469 | Danny Hill | 1 | 1 | 9 | 0 | 0.04 |
| 5470 | Denise Fisher | 1 | 1 | 9 | 0 | 0.04 |
| 5471 | Elizabeth Stone | 1 | 1 | 9 | 0 | 0.04 |
| 5472 | Frank Shaffer | 1 | 1 | 9 | 0 | 0.04 |
| 5473 | Gang Wu | 1 | 1 | 9 | 0 | 0.04 |
| 5474 | Guiying Wan | 1 | 1 | 9 | 0 | 0.04 |
| 5475 | Jacob Martin | 1 | 1 | 9 | 0 | 0.04 |
| 5476 | John Guzman II | 1 | 1 | 9 | 0 | 0.04 |
| 5477 | Jordan Thomas | 1 | 1 | 9 | 0 | 0.04 |
| 5478 | Joy Fletcher | 1 | 1 | 9 | 0 | 0.04 |
| 5479 | Karen Graham | 1 | 1 | 9 | 0 | 0.04 |
| 5480 | Katherine Bradley | 1 | 1 | 9 | 0 | 0.04 |
| 5481 | Kevin Rush | 1 | 1 | 9 | 0 | 0.04 |
| 5482 | Kimberly Collins | 1 | 1 | 9 | 0 | 0.04 |
| 5483 | Kimberly Jordan | 1 | 1 | 9 | 0 | 0.04 |
| 5484 | Kimberly Young | 1 | 1 | 9 | 0 | 0.04 |
| 5485 | Kristy Nelson | 1 | 1 | 9 | 0 | 0.04 |
| 5486 | Lara Horrocks | 1 | 1 | 9 | 0 | 0.04 |
| 5487 | Larry Jones | 1 | 1 | 9 | 0 | 0.04 |
| 5488 | Laura Rodriguez | 1 | 1 | 9 | 0 | 0.04 |
| 5489 | Lisa Nunez | 1 | 1 | 9 | 0 | 0.04 |
| 5490 | Lola Vermeulen | 1 | 1 | 9 | 0 | 0.04 |
| 5491 | Marc Andersen | 1 | 1 | 9 | 0 | 0.04 |
| 5492 | Mathew Schultz | 1 | 1 | 9 | 0 | 0.04 |
| 5493 | Matthew Hill | 1 | 1 | 9 | 0 | 0.04 |
| 5494 | Michelle Hensley | 1 | 1 | 9 | 0 | 0.04 |
| 5495 | Pamela Rollins | 1 | 1 | 9 | 0 | 0.04 |
| 5496 | Patricia Fisher | 1 | 1 | 9 | 0 | 0.04 |
| 5497 | Paul Lopez | 1 | 1 | 9 | 0 | 0.04 |
| 5498 | Peter Garcia | 1 | 1 | 9 | 0 | 0.04 |
| 5499 | Qiang Su | 1 | 1 | 9 | 0 | 0.04 |
| 5500 | Qiang Wen | 1 | 1 | 9 | 0 | 0.04 |
| 5501 | Robert Brown | 1 | 1 | 9 | 0 | 0.04 |
| 5502 | Rose Dean | 1 | 1 | 9 | 0 | 0.04 |
| 5503 | Samuel Ryan | 1 | 1 | 9 | 0 | 0.04 |
| 5504 | Sean Peck | 1 | 1 | 9 | 0 | 0.04 |
| 5505 | Sosimo Vila Bayona | 1 | 1 | 9 | 0 | 0.04 |
| 5506 | Travis Thompson | 1 | 1 | 9 | 0 | 0.04 |
| 5507 | Xiulan Xia | 1 | 1 | 9 | 0 | 0.04 |
| 5508 | Yong Xiong | 1 | 1 | 9 | 0 | 0.04 |
| 5509 | Adrianna Kurc | 1 | 1 | 5 | 1 | 0.04 |
| 5510 | Advika Ramakrishnan | 1 | 1 | 5 | 1 | 0.04 |
| 5511 | Alejandro Montenegro-Palomino | 1 | 1 | 5 | 1 | 0.04 |
| 5512 | Alexa Thomas | 1 | 1 | 5 | 1 | 0.04 |
| 5513 | Alonso del Benítez | 1 | 1 | 5 | 1 | 0.04 |
| 5514 | Amleto Fittipaldi | 1 | 1 | 5 | 1 | 0.04 |
| 5515 | Amy Mejia | 1 | 1 | 5 | 1 | 0.04 |
| 5516 | Anahi Sachdeva | 1 | 1 | 5 | 1 | 0.04 |
| 5517 | Anastazja Łuczyk | 1 | 1 | 5 | 1 | 0.04 |
| 5518 | Angela Hernandez | 1 | 1 | 5 | 1 | 0.04 |
| 5519 | Antonella Moschino | 1 | 1 | 5 | 1 | 0.04 |
| 5520 | Antonietta Chittolini | 1 | 1 | 5 | 1 | 0.04 |
| 5521 | April Welch | 1 | 1 | 5 | 1 | 0.04 |
| 5522 | Arsenio Berengario | 1 | 1 | 5 | 1 | 0.04 |
| 5523 | Aurélie de la Lucas | 1 | 1 | 5 | 1 | 0.04 |
| 5524 | Bethany Thompson | 1 | 1 | 5 | 1 | 0.04 |
| 5525 | Bianca Mentzel | 1 | 1 | 5 | 1 | 0.04 |
| 5526 | Birger Klemt | 1 | 1 | 5 | 1 | 0.04 |
| 5527 | Caleb Long | 1 | 1 | 5 | 1 | 0.04 |
| 5528 | Carlito Martí Jaume | 1 | 1 | 5 | 1 | 0.04 |
| 5529 | Carolyn Sharp | 1 | 1 | 5 | 1 | 0.04 |
| 5530 | Carsten Heinz | 1 | 1 | 5 | 1 | 0.04 |
| 5531 | Casey Scott | 1 | 1 | 5 | 1 | 0.04 |
| 5532 | Cassandra Zito | 1 | 1 | 5 | 1 | 0.04 |
| 5533 | Caterina Mercadante-Munari | 1 | 1 | 5 | 1 | 0.04 |
| 5534 | Cheryl White | 1 | 1 | 5 | 1 | 0.04 |
| 5535 | Chiyo Hashimoto | 1 | 1 | 5 | 1 | 0.04 |
| 5536 | Christina Martin | 1 | 1 | 5 | 1 | 0.04 |
| 5537 | Christine Olson | 1 | 1 | 5 | 1 | 0.04 |
| 5538 | Corey Stephens | 1 | 1 | 5 | 1 | 0.04 |
| 5539 | Craig Gonzalez | 1 | 1 | 5 | 1 | 0.04 |
| 5540 | Dagmara Pasztaleniec | 1 | 1 | 5 | 1 | 0.04 |
| 5541 | Daniel Harrington | 1 | 1 | 5 | 1 | 0.04 |
| 5542 | Danielle Ball | 1 | 1 | 5 | 1 | 0.04 |
| 5543 | Dawn Martinez | 1 | 1 | 5 | 1 | 0.04 |
| 5544 | Deanna Johnson | 1 | 1 | 5 | 1 | 0.04 |
| 5545 | Deanna Williams | 1 | 1 | 5 | 1 | 0.04 |
| 5546 | Debbie Hall | 1 | 1 | 5 | 1 | 0.04 |
| 5547 | Diana Lewis | 1 | 1 | 5 | 1 | 0.04 |
| 5548 | Ela Dara | 1 | 1 | 5 | 1 | 0.04 |
| 5549 | Elba Zaragoza-Doménech | 1 | 1 | 5 | 1 | 0.04 |
| 5550 | Eliana Marini | 1 | 1 | 5 | 1 | 0.04 |
| 5551 | Elizabeth Baker | 1 | 1 | 5 | 1 | 0.04 |
| 5552 | Elizabeth Brown | 1 | 1 | 5 | 1 | 0.04 |
| 5553 | Elizabeth Webb | 1 | 1 | 5 | 1 | 0.04 |
| 5554 | Ernestine Franke-Kade | 1 | 1 | 5 | 1 | 0.04 |
| 5555 | Eugenia Lindner | 1 | 1 | 5 | 1 | 0.04 |
| 5556 | Fang Zeng | 1 | 1 | 5 | 1 | 0.04 |
| 5557 | Gabriel Silva | 1 | 1 | 5 | 1 | 0.04 |
| 5558 | Garrett Salazar | 1 | 1 | 5 | 1 | 0.04 |
| 5559 | George Snyder | 1 | 1 | 5 | 1 | 0.04 |
| 5560 | Gesine Gehringer-Rogner | 1 | 1 | 5 | 1 | 0.04 |
| 5561 | Giampiero Lombroso | 1 | 1 | 5 | 1 | 0.04 |
| 5562 | Gianfranco Trentini | 1 | 1 | 5 | 1 | 0.04 |
| 5563 | Gianluca Barberini | 1 | 1 | 5 | 1 | 0.04 |
| 5564 | Gordana Schwital | 1 | 1 | 5 | 1 | 0.04 |
| 5565 | Gregory Huffman | 1 | 1 | 5 | 1 | 0.04 |
| 5566 | Griselda Renier-Mozart | 1 | 1 | 5 | 1 | 0.04 |
| 5567 | Hans-Willi Henschel | 1 | 1 | 5 | 1 | 0.04 |
| 5568 | Hansh Dyal | 1 | 1 | 5 | 1 | 0.04 |
| 5569 | Heinz-Georg Segebahn | 1 | 1 | 5 | 1 | 0.04 |
| 5570 | Henrike Pärtzelt | 1 | 1 | 5 | 1 | 0.04 |
| 5571 | Herminia Vazquez-Sainz | 1 | 1 | 5 | 1 | 0.04 |
| 5572 | Herr Detlef Geißler | 1 | 1 | 5 | 1 | 0.04 |
| 5573 | Herr Ulrich Gieß | 1 | 1 | 5 | 1 | 0.04 |
| 5574 | Hidde Huisman | 1 | 1 | 5 | 1 | 0.04 |
| 5575 | Indrajit Borra | 1 | 1 | 5 | 1 | 0.04 |
| 5576 | Isaac Joubert | 1 | 1 | 5 | 1 | 0.04 |
| 5577 | Itziar Mata Marqués | 1 | 1 | 5 | 1 | 0.04 |
| 5578 | Ivana Bains | 1 | 1 | 5 | 1 | 0.04 |
| 5579 | Iwo Olbrych | 1 | 1 | 5 | 1 | 0.04 |
| 5580 | Iwo Zbrzeźniak | 1 | 1 | 5 | 1 | 0.04 |
| 5581 | James Bauer | 1 | 1 | 5 | 1 | 0.04 |
| 5582 | James Munoz | 1 | 1 | 5 | 1 | 0.04 |
| 5583 | Janina Mazik | 1 | 1 | 5 | 1 | 0.04 |
| 5584 | Jared Banks | 1 | 1 | 5 | 1 | 0.04 |
| 5585 | Jasmine Thompson | 1 | 1 | 5 | 1 | 0.04 |
| 5586 | Jason Baker | 1 | 1 | 5 | 1 | 0.04 |
| 5587 | Jayan Chandran | 1 | 1 | 5 | 1 | 0.04 |
| 5588 | Jeremi Kwarciak | 1 | 1 | 5 | 1 | 0.04 |
| 5589 | Jeremy Hahn | 1 | 1 | 5 | 1 | 0.04 |
| 5590 | Jessica Parsons | 1 | 1 | 5 | 1 | 0.04 |
| 5591 | Jie Zeng | 1 | 1 | 5 | 1 | 0.04 |
| 5592 | Joann Smith | 1 | 1 | 5 | 1 | 0.04 |
| 5593 | Joel Miller | 1 | 1 | 5 | 1 | 0.04 |
| 5594 | Johannes de Vries | 1 | 1 | 5 | 1 | 0.04 |
| 5595 | Jolanta Schlosser | 1 | 1 | 5 | 1 | 0.04 |
| 5596 | Jonathan May | 1 | 1 | 5 | 1 | 0.04 |
| 5597 | Jorge Ross | 1 | 1 | 5 | 1 | 0.04 |
| 5598 | Jose Sanders | 1 | 1 | 5 | 1 | 0.04 |
| 5599 | Joseph Wheeler | 1 | 1 | 5 | 1 | 0.04 |
| 5600 | Julie Lane | 1 | 1 | 5 | 1 | 0.04 |
| 5601 | Józef Niewiara | 1 | 1 | 5 | 1 | 0.04 |
| 5602 | Kalina Fidor | 1 | 1 | 5 | 1 | 0.04 |
| 5603 | Katherine Wang | 1 | 1 | 5 | 1 | 0.04 |
| 5604 | Kathleen Russo | 1 | 1 | 5 | 1 | 0.04 |
| 5605 | Kelly Sanders | 1 | 1 | 5 | 1 | 0.04 |
| 5606 | Klara Betlej | 1 | 1 | 5 | 1 | 0.04 |
| 5607 | Kornelia Raczkiewicz | 1 | 1 | 5 | 1 | 0.04 |
| 5608 | Krista Rogge | 1 | 1 | 5 | 1 | 0.04 |
| 5609 | Kristina Taylor | 1 | 1 | 5 | 1 | 0.04 |
| 5610 | Leocadia Falcón Diez | 1 | 1 | 5 | 1 | 0.04 |
| 5611 | Lucia Corradi | 1 | 1 | 5 | 1 | 0.04 |
| 5612 | Manikya Badal | 1 | 1 | 5 | 1 | 0.04 |
| 5613 | Manon Voisin | 1 | 1 | 5 | 1 | 0.04 |
| 5614 | Marcelina Kosno | 1 | 1 | 5 | 1 | 0.04 |
| 5615 | Mateusz Perczak | 1 | 1 | 5 | 1 | 0.04 |
| 5616 | Matthew Hall | 1 | 1 | 5 | 1 | 0.04 |
| 5617 | Matthew Murphy | 1 | 1 | 5 | 1 | 0.04 |
| 5618 | Maurycy Bohdanowicz | 1 | 1 | 5 | 1 | 0.04 |
| 5619 | Mechthilde Kühnert | 1 | 1 | 5 | 1 | 0.04 |
| 5620 | Megan Mcclure | 1 | 1 | 5 | 1 | 0.04 |
| 5621 | Melissa Soto | 1 | 1 | 5 | 1 | 0.04 |
| 5622 | Michael Keller | 1 | 1 | 5 | 1 | 0.04 |
| 5623 | Michael Thompson | 1 | 1 | 5 | 1 | 0.04 |
| 5624 | Micheal Martin | 1 | 1 | 5 | 1 | 0.04 |
| 5625 | Michel Pichon | 1 | 1 | 5 | 1 | 0.04 |
| 5626 | Michelle Barnes | 1 | 1 | 5 | 1 | 0.04 |
| 5627 | Nacio Joel Corral Domingo | 1 | 1 | 5 | 1 | 0.04 |
| 5628 | Natasha Duncan | 1 | 1 | 5 | 1 | 0.04 |
| 5629 | Nathaniel Alvarado | 1 | 1 | 5 | 1 | 0.04 |
| 5630 | Nicola Napolitano | 1 | 1 | 5 | 1 | 0.04 |
| 5631 | Nicole Bowers | 1 | 1 | 5 | 1 | 0.04 |
| 5632 | Nicole Mccormick | 1 | 1 | 5 | 1 | 0.04 |
| 5633 | Nina Pareto | 1 | 1 | 5 | 1 | 0.04 |
| 5634 | Nishith Sachar | 1 | 1 | 5 | 1 | 0.04 |
| 5635 | Nitya Dass | 1 | 1 | 5 | 1 | 0.04 |
| 5636 | Nout Zijlmans | 1 | 1 | 5 | 1 | 0.04 |
| 5637 | Nynke Corstiaens | 1 | 1 | 5 | 1 | 0.04 |
| 5638 | Octavia Gilabert León | 1 | 1 | 5 | 1 | 0.04 |
| 5639 | Olivia Solomon | 1 | 1 | 5 | 1 | 0.04 |
| 5640 | Onkar Shankar | 1 | 1 | 5 | 1 | 0.04 |
| 5641 | Osamu Goto | 1 | 1 | 5 | 1 | 0.04 |
| 5642 | Pam Cunningham | 1 | 1 | 5 | 1 | 0.04 |
| 5643 | Paola Täsche | 1 | 1 | 5 | 1 | 0.04 |
| 5644 | Patrick Geisler | 1 | 1 | 5 | 1 | 0.04 |
| 5645 | Patrick Nguyen | 1 | 1 | 5 | 1 | 0.04 |
| 5646 | Perry Lopez | 1 | 1 | 5 | 1 | 0.04 |
| 5647 | Peter Collins | 1 | 1 | 5 | 1 | 0.04 |
| 5648 | Ping Long | 1 | 1 | 5 | 1 | 0.04 |
| 5649 | Piotr Wacław | 1 | 1 | 5 | 1 | 0.04 |
| 5650 | Pranay Mahajan | 1 | 1 | 5 | 1 | 0.04 |
| 5651 | Rafał Raba | 1 | 1 | 5 | 1 | 0.04 |
| 5652 | Rhonda Mcgee | 1 | 1 | 5 | 1 | 0.04 |
| 5653 | Rika Yamamoto | 1 | 1 | 5 | 1 | 0.04 |
| 5654 | Robert Cannon | 1 | 1 | 5 | 1 | 0.04 |
| 5655 | Robert King | 1 | 1 | 5 | 1 | 0.04 |
| 5656 | Robert Pugh | 1 | 1 | 5 | 1 | 0.04 |
| 5657 | Roksana Kurzyna | 1 | 1 | 5 | 1 | 0.04 |
| 5658 | Sara Jover Iglesias | 1 | 1 | 5 | 1 | 0.04 |
| 5659 | Sarah Ward | 1 | 1 | 5 | 1 | 0.04 |
| 5660 | Sean Rush | 1 | 1 | 5 | 1 | 0.04 |
| 5661 | Sebastiano Torlonia | 1 | 1 | 5 | 1 | 0.04 |
| 5662 | Segismundo Hoyos Múgica | 1 | 1 | 5 | 1 | 0.04 |
| 5663 | Sharon Bray | 1 | 1 | 5 | 1 | 0.04 |
| 5664 | Sharon Mcclain | 1 | 1 | 5 | 1 | 0.04 |
| 5665 | Shayak Chakraborty | 1 | 1 | 5 | 1 | 0.04 |
| 5666 | Sheila Cox | 1 | 1 | 5 | 1 | 0.04 |
| 5667 | Sheri Calhoun | 1 | 1 | 5 | 1 | 0.04 |
| 5668 | Sibylla Beyer | 1 | 1 | 5 | 1 | 0.04 |
| 5669 | Sibylla Heintze | 1 | 1 | 5 | 1 | 0.04 |
| 5670 | Susanne Pierre | 1 | 1 | 5 | 1 | 0.04 |
| 5671 | Tammy Wilcox | 1 | 1 | 5 | 1 | 0.04 |
| 5672 | Terry Clark | 1 | 1 | 5 | 1 | 0.04 |
| 5673 | Timothy Lopez | 1 | 1 | 5 | 1 | 0.04 |
| 5674 | Tiya Kota | 1 | 1 | 5 | 1 | 0.04 |
| 5675 | Umang Uppal | 1 | 1 | 5 | 1 | 0.04 |
| 5676 | William de la Valentin | 1 | 1 | 5 | 1 | 0.04 |
| 5677 | Xavier Pierre | 1 | 1 | 5 | 1 | 0.04 |
| 5678 | Yoko Nishimura | 1 | 1 | 5 | 1 | 0.04 |
| 5679 | Yong Huang | 1 | 1 | 5 | 1 | 0.04 |
| 5680 | Yong Ma | 1 | 1 | 5 | 1 | 0.04 |
| 5681 | Yong Yin | 1 | 1 | 5 | 1 | 0.04 |
| 5682 | Zacharie Morin | 1 | 1 | 5 | 1 | 0.04 |
| 5683 | Zara Choudhury | 1 | 1 | 5 | 1 | 0.04 |
| 5684 | Zeeshan Kuruvilla | 1 | 1 | 5 | 1 | 0.04 |
| 5685 | Aaron Medina | 1 | 1 | 8 | 0 | 0.04 |
| 5686 | Alfonso Bähr | 1 | 1 | 8 | 0 | 0.04 |
| 5687 | Andrew Ellison | 1 | 1 | 8 | 0 | 0.04 |
| 5688 | Annelise Berger | 1 | 1 | 8 | 0 | 0.04 |
| 5689 | Aurélie Traore de Grondin | 1 | 1 | 8 | 0 | 0.04 |
| 5690 | Billy Martinez | 1 | 1 | 8 | 0 | 0.04 |
| 5691 | Brian Mathis | 1 | 1 | 8 | 0 | 0.04 |
| 5692 | Brian Richard | 1 | 1 | 8 | 0 | 0.04 |
| 5693 | Candice Avila | 1 | 1 | 8 | 0 | 0.04 |
| 5694 | Carl Brown | 1 | 1 | 8 | 0 | 0.04 |
| 5695 | Carrie Smith | 1 | 1 | 8 | 0 | 0.04 |
| 5696 | Charles Thomas | 1 | 1 | 8 | 0 | 0.04 |
| 5697 | Curtis Cooper | 1 | 1 | 8 | 0 | 0.04 |
| 5698 | Deanna Green | 1 | 1 | 8 | 0 | 0.04 |
| 5699 | Douglas Gray | 1 | 1 | 8 | 0 | 0.04 |
| 5700 | Drew Green | 1 | 1 | 8 | 0 | 0.04 |
| 5701 | Edward Gutierrez | 1 | 1 | 8 | 0 | 0.04 |
| 5702 | Gang Qiu | 1 | 1 | 8 | 0 | 0.04 |
| 5703 | Gregory Morgan | 1 | 1 | 8 | 0 | 0.04 |
| 5704 | Gudula Mitschke-Reuter | 1 | 1 | 8 | 0 | 0.04 |
| 5705 | Henry Ortega | 1 | 1 | 8 | 0 | 0.04 |
| 5706 | Holly Garcia | 1 | 1 | 8 | 0 | 0.04 |
| 5707 | Hubert Oderwald | 1 | 1 | 8 | 0 | 0.04 |
| 5708 | Hélène Lévêque | 1 | 1 | 8 | 0 | 0.04 |
| 5709 | Isaiah Gonzales | 1 | 1 | 8 | 0 | 0.04 |
| 5710 | Jason Lewis | 1 | 1 | 8 | 0 | 0.04 |
| 5711 | Jennifer Acosta | 1 | 1 | 8 | 0 | 0.04 |
| 5712 | Jeremy Watkins | 1 | 1 | 8 | 0 | 0.04 |
| 5713 | John Brooks | 1 | 1 | 8 | 0 | 0.04 |
| 5714 | Joshua Holmes | 1 | 1 | 8 | 0 | 0.04 |
| 5715 | Justin Carroll | 1 | 1 | 8 | 0 | 0.04 |
| 5716 | Karen Munoz | 1 | 1 | 8 | 0 | 0.04 |
| 5717 | Katie Smith | 1 | 1 | 8 | 0 | 0.04 |
| 5718 | Kimberly Foster | 1 | 1 | 8 | 0 | 0.04 |
| 5719 | Kimberly Kim | 1 | 1 | 8 | 0 | 0.04 |
| 5720 | Kristin Thomas | 1 | 1 | 8 | 0 | 0.04 |
| 5721 | Laura Howard | 1 | 1 | 8 | 0 | 0.04 |
| 5722 | Laura Johnson | 1 | 1 | 8 | 0 | 0.04 |
| 5723 | Lilo Christoph | 1 | 1 | 8 | 0 | 0.04 |
| 5724 | Lucas Jose Manuel Arnaiz Pinedo | 1 | 1 | 8 | 0 | 0.04 |
| 5725 | Maggie-Margot Vallée | 1 | 1 | 8 | 0 | 0.04 |
| 5726 | Mary Turner | 1 | 1 | 8 | 0 | 0.04 |
| 5727 | Megan Fox | 1 | 1 | 8 | 0 | 0.04 |
| 5728 | Michael Gibbs | 1 | 1 | 8 | 0 | 0.04 |
| 5729 | Miguel Shelton | 1 | 1 | 8 | 0 | 0.04 |
| 5730 | Nicole Anderson | 1 | 1 | 8 | 0 | 0.04 |
| 5731 | Olivier Munoz | 1 | 1 | 8 | 0 | 0.04 |
| 5732 | Paul Williams | 1 | 1 | 8 | 0 | 0.04 |
| 5733 | Phillip Stone | 1 | 1 | 8 | 0 | 0.04 |
| 5734 | Qiang Jin | 1 | 1 | 8 | 0 | 0.04 |
| 5735 | Rachel Hogan | 1 | 1 | 8 | 0 | 0.04 |
| 5736 | Ramona Petruzzi | 1 | 1 | 8 | 0 | 0.04 |
| 5737 | Raven Bowman | 1 | 1 | 8 | 0 | 0.04 |
| 5738 | Rebecca Ramirez | 1 | 1 | 8 | 0 | 0.04 |
| 5739 | Sara Estefanía Acedo Caro | 1 | 1 | 8 | 0 | 0.04 |
| 5740 | Sean Walters | 1 | 1 | 8 | 0 | 0.04 |
| 5741 | Steven Harris | 1 | 1 | 8 | 0 | 0.04 |
| 5742 | Tara Ortiz | 1 | 1 | 8 | 0 | 0.04 |
| 5743 | Timothy Beck | 1 | 1 | 8 | 0 | 0.04 |
| 5744 | Tracy Camacho | 1 | 1 | 8 | 0 | 0.04 |
| 5745 | William Peck | 1 | 1 | 8 | 0 | 0.04 |
| 5746 | Xiulan Kong | 1 | 1 | 8 | 0 | 0.04 |
| 5747 | Xiuying Gao | 1 | 1 | 8 | 0 | 0.04 |
| 5748 | Leo Hamilton | 2 | 0 | 5 | 1 | 0.04 |
| 5749 | Noah Bennett | 2 | 0 | 5 | 1 | 0.04 |
| 5750 | Aaron Martinez | 1 | 1 | 4 | 1 | 0.04 |
| 5751 | Adriana Trobbiani | 1 | 1 | 4 | 1 | 0.04 |
| 5752 | Advik Singh | 1 | 1 | 4 | 1 | 0.04 |
| 5753 | Akira Kobayashi | 1 | 1 | 4 | 1 | 0.04 |
| 5754 | Alicia Smith | 1 | 1 | 4 | 1 | 0.04 |
| 5755 | Alison Armstrong | 1 | 1 | 4 | 1 | 0.04 |
| 5756 | Allison Harris | 1 | 1 | 4 | 1 | 0.04 |
| 5757 | Andrew Barnes | 1 | 1 | 4 | 1 | 0.04 |
| 5758 | Angela Greene | 1 | 1 | 4 | 1 | 0.04 |
| 5759 | Ann Anderson | 1 | 1 | 4 | 1 | 0.04 |
| 5760 | Anouk Rivière | 1 | 1 | 4 | 1 | 0.04 |
| 5761 | Anthony Erickson | 1 | 1 | 4 | 1 | 0.04 |
| 5762 | April Crosby | 1 | 1 | 4 | 1 | 0.04 |
| 5763 | April Ortiz | 1 | 1 | 4 | 1 | 0.04 |
| 5764 | Ben le Gallen | 1 | 1 | 4 | 1 | 0.04 |
| 5765 | Benjamin Rogers | 1 | 1 | 4 | 1 | 0.04 |
| 5766 | Blake Melton | 1 | 1 | 4 | 1 | 0.04 |
| 5767 | Brandon Trujillo | 1 | 1 | 4 | 1 | 0.04 |
| 5768 | Brandon Williams | 1 | 1 | 4 | 1 | 0.04 |
| 5769 | Dale Stewart | 1 | 1 | 4 | 1 | 0.04 |
| 5770 | David Smith | 1 | 1 | 4 | 1 | 0.04 |
| 5771 | Deborah White | 1 | 1 | 4 | 1 | 0.04 |
| 5772 | Donna Anderson | 1 | 1 | 4 | 1 | 0.04 |
| 5773 | Douglas Stout | 1 | 1 | 4 | 1 | 0.04 |
| 5774 | Edward Ellis | 1 | 1 | 4 | 1 | 0.04 |
| 5775 | Elizabeth Phillips | 1 | 1 | 4 | 1 | 0.04 |
| 5776 | Fang Ye | 1 | 1 | 4 | 1 | 0.04 |
| 5777 | Farhan Bansal | 1 | 1 | 4 | 1 | 0.04 |
| 5778 | Franziska Lindau | 1 | 1 | 4 | 1 | 0.04 |
| 5779 | Gerold Sontag | 1 | 1 | 4 | 1 | 0.04 |
| 5780 | Graziella Marenzio-Scialpi | 1 | 1 | 4 | 1 | 0.04 |
| 5781 | Guiying Wen | 1 | 1 | 4 | 1 | 0.04 |
| 5782 | Heidelore Meister | 1 | 1 | 4 | 1 | 0.04 |
| 5783 | Herr Alexander Eckbauer | 1 | 1 | 4 | 1 | 0.04 |
| 5784 | Holly Lucero | 1 | 1 | 4 | 1 | 0.04 |
| 5785 | Jacqueline Hörle | 1 | 1 | 4 | 1 | 0.04 |
| 5786 | James Copeland | 1 | 1 | 4 | 1 | 0.04 |
| 5787 | Jessica Bernard | 1 | 1 | 4 | 1 | 0.04 |
| 5788 | Joan Brown | 1 | 1 | 4 | 1 | 0.04 |
| 5789 | Jocelyn Hall | 1 | 1 | 4 | 1 | 0.04 |
| 5790 | John Carlson | 1 | 1 | 4 | 1 | 0.04 |
| 5791 | Joseph Smith | 1 | 1 | 4 | 1 | 0.04 |
| 5792 | Joyce Norris | 1 | 1 | 4 | 1 | 0.04 |
| 5793 | Kashvi Dutt | 1 | 1 | 4 | 1 | 0.04 |
| 5794 | Katrina Guzman | 1 | 1 | 4 | 1 | 0.04 |
| 5795 | Kayla Grimes | 1 | 1 | 4 | 1 | 0.04 |
| 5796 | Kimaya Aggarwal | 1 | 1 | 4 | 1 | 0.04 |
| 5797 | Krish Thaker | 1 | 1 | 4 | 1 | 0.04 |
| 5798 | Kyle Johnson | 1 | 1 | 4 | 1 | 0.04 |
| 5799 | Leonie Kabus | 1 | 1 | 4 | 1 | 0.04 |
| 5800 | Leslie Page | 1 | 1 | 4 | 1 | 0.04 |
| 5801 | Lindsey Jackson | 1 | 1 | 4 | 1 | 0.04 |
| 5802 | Lucas Aguilar | 1 | 1 | 4 | 1 | 0.04 |
| 5803 | Maik Eckbauer | 1 | 1 | 4 | 1 | 0.04 |
| 5804 | Maria Priuli | 1 | 1 | 4 | 1 | 0.04 |
| 5805 | Marianna Drózd | 1 | 1 | 4 | 1 | 0.04 |
| 5806 | Mariola Häring | 1 | 1 | 4 | 1 | 0.04 |
| 5807 | Mark Schmidt | 1 | 1 | 4 | 1 | 0.04 |
| 5808 | Martin Frederick | 1 | 1 | 4 | 1 | 0.04 |
| 5809 | Mary Freeman | 1 | 1 | 4 | 1 | 0.04 |
| 5810 | Mary Gutierrez | 1 | 1 | 4 | 1 | 0.04 |
| 5811 | Matthew James | 1 | 1 | 4 | 1 | 0.04 |
| 5812 | Micha Weinhage | 1 | 1 | 4 | 1 | 0.04 |
| 5813 | Michael Wise | 1 | 1 | 4 | 1 | 0.04 |
| 5814 | Michael Wright | 1 | 1 | 4 | 1 | 0.04 |
| 5815 | Michelle Caldwell | 1 | 1 | 4 | 1 | 0.04 |
| 5816 | Miki Maeda | 1 | 1 | 4 | 1 | 0.04 |
| 5817 | Nelly Austermühle | 1 | 1 | 4 | 1 | 0.04 |
| 5818 | Nisa van de Biezenbos | 1 | 1 | 4 | 1 | 0.04 |
| 5819 | Nomadic Resonance | 1 | 1 | 4 | 1 | 0.04 |
| 5820 | Olivie Sauvage | 1 | 1 | 4 | 1 | 0.04 |
| 5821 | Olivier Antoine | 1 | 1 | 4 | 1 | 0.04 |
| 5822 | Pamela Griffin | 1 | 1 | 4 | 1 | 0.04 |
| 5823 | Paola Scheuermann | 1 | 1 | 4 | 1 | 0.04 |
| 5824 | Patrick Bertin | 1 | 1 | 4 | 1 | 0.04 |
| 5825 | Patrick Lindsey | 1 | 1 | 4 | 1 | 0.04 |
| 5826 | Pihu Ahuja | 1 | 1 | 4 | 1 | 0.04 |
| 5827 | Prisha Varkey | 1 | 1 | 4 | 1 | 0.04 |
| 5828 | Rebecca Austin | 1 | 1 | 4 | 1 | 0.04 |
| 5829 | Rebecca Webb | 1 | 1 | 4 | 1 | 0.04 |
| 5830 | Rhea Bajwa | 1 | 1 | 4 | 1 | 0.04 |
| 5831 | Rhonda Knox | 1 | 1 | 4 | 1 | 0.04 |
| 5832 | Riaan Balan | 1 | 1 | 4 | 1 | 0.04 |
| 5833 | Robert Jennings | 1 | 1 | 4 | 1 | 0.04 |
| 5834 | Rodney Moss | 1 | 1 | 4 | 1 | 0.04 |
| 5835 | Russell Ruiz | 1 | 1 | 4 | 1 | 0.04 |
| 5836 | Samar Sarma | 1 | 1 | 4 | 1 | 0.04 |
| 5837 | Sarah Hayes | 1 | 1 | 4 | 1 | 0.04 |
| 5838 | Scott Villa | 1 | 1 | 4 | 1 | 0.04 |
| 5839 | Shalv Dass | 1 | 1 | 4 | 1 | 0.04 |
| 5840 | Sophie Broeckx | 1 | 1 | 4 | 1 | 0.04 |
| 5841 | Théophile de Carlier | 1 | 1 | 4 | 1 | 0.04 |
| 5842 | Valeska Heinrich | 1 | 1 | 4 | 1 | 0.04 |
| 5843 | Vanessa King | 1 | 1 | 4 | 1 | 0.04 |
| 5844 | Virginia White | 1 | 1 | 4 | 1 | 0.04 |
| 5845 | William Burton | 1 | 1 | 4 | 1 | 0.04 |
| 5846 | Xiulan Han | 1 | 1 | 4 | 1 | 0.04 |
| 5847 | Yara Robbrechts Bruijne | 1 | 1 | 4 | 1 | 0.04 |
| 5848 | Zaina Zacharia | 1 | 1 | 4 | 1 | 0.04 |
| 5849 | Christine Robbins | 1 | 0 | 17 | 2 | 0.04 |
| 5850 | Dennis Hill PhD | 1 | 0 | 17 | 2 | 0.04 |
| 5851 | Amy Gonzalez | 1 | 1 | 7 | 0 | 0.04 |
| 5852 | Annunziata Disdero | 1 | 1 | 7 | 0 | 0.04 |
| 5853 | Brian Nguyen | 1 | 1 | 7 | 0 | 0.04 |
| 5854 | Bryan Matthews | 1 | 1 | 7 | 0 | 0.04 |
| 5855 | Bryan Shaw | 1 | 1 | 7 | 0 | 0.04 |
| 5856 | Camilla Zaccagnini-Bertoni | 1 | 1 | 7 | 0 | 0.04 |
| 5857 | Carlos Cannon | 1 | 1 | 7 | 0 | 0.04 |
| 5858 | Carrie Perry | 1 | 1 | 7 | 0 | 0.04 |
| 5859 | Catherine Black | 1 | 1 | 7 | 0 | 0.04 |
| 5860 | Christina Robinson | 1 | 1 | 7 | 0 | 0.04 |
| 5861 | Christopher Romero | 1 | 1 | 7 | 0 | 0.04 |
| 5862 | Diana Trujillo | 1 | 1 | 7 | 0 | 0.04 |
| 5863 | Emilio Farnese | 1 | 1 | 7 | 0 | 0.04 |
| 5864 | Fortunata Zeffirelli | 1 | 1 | 7 | 0 | 0.04 |
| 5865 | Francisco Campbell | 1 | 1 | 7 | 0 | 0.04 |
| 5866 | Friedbert Stey | 1 | 1 | 7 | 0 | 0.04 |
| 5867 | Gary Wallace | 1 | 1 | 7 | 0 | 0.04 |
| 5868 | Gina Cooper | 1 | 1 | 7 | 0 | 0.04 |
| 5869 | Giustino Carocci | 1 | 1 | 7 | 0 | 0.04 |
| 5870 | Guiying Li | 1 | 1 | 7 | 0 | 0.04 |
| 5871 | Hannah Payne | 1 | 1 | 7 | 0 | 0.04 |
| 5872 | Hannah Richards | 1 | 1 | 7 | 0 | 0.04 |
| 5873 | Hans-H. Jacobi Jäckel | 1 | 1 | 7 | 0 | 0.04 |
| 5874 | Harold Gutierrez | 1 | 1 | 7 | 0 | 0.04 |
| 5875 | Isabella Cook | 1 | 1 | 7 | 0 | 0.04 |
| 5876 | Jacopo Vianello | 1 | 1 | 7 | 0 | 0.04 |
| 5877 | Jesus Rivas | 1 | 1 | 7 | 0 | 0.04 |
| 5878 | Jie Yu | 1 | 1 | 7 | 0 | 0.04 |
| 5879 | Jill Goodman | 1 | 1 | 7 | 0 | 0.04 |
| 5880 | Job Mahieu | 1 | 1 | 7 | 0 | 0.04 |
| 5881 | Jonathan Horne | 1 | 1 | 7 | 0 | 0.04 |
| 5882 | Joseph Maxwell | 1 | 1 | 7 | 0 | 0.04 |
| 5883 | Juan Cui | 1 | 1 | 7 | 0 | 0.04 |
| 5884 | Juan Xie | 1 | 1 | 7 | 0 | 0.04 |
| 5885 | Kayla Taylor | 1 | 1 | 7 | 0 | 0.04 |
| 5886 | Kim Gonzalez | 1 | 1 | 7 | 0 | 0.04 |
| 5887 | Lara Scaramucci-Santi | 1 | 1 | 7 | 0 | 0.04 |
| 5888 | Laura Ward | 1 | 1 | 7 | 0 | 0.04 |
| 5889 | Laura Wolf | 1 | 1 | 7 | 0 | 0.04 |
| 5890 | Linda Ward | 1 | 1 | 7 | 0 | 0.04 |
| 5891 | Lindsay Marsh | 1 | 1 | 7 | 0 | 0.04 |
| 5892 | Marc Drake | 1 | 1 | 7 | 0 | 0.04 |
| 5893 | Maria Merritt | 1 | 1 | 7 | 0 | 0.04 |
| 5894 | Mary Griffin | 1 | 1 | 7 | 0 | 0.04 |
| 5895 | Matthew Gardner | 1 | 1 | 7 | 0 | 0.04 |
| 5896 | Mattia Pepe | 1 | 1 | 7 | 0 | 0.04 |
| 5897 | Michael Gordon | 1 | 1 | 7 | 0 | 0.04 |
| 5898 | Monica Dean | 1 | 1 | 7 | 0 | 0.04 |
| 5899 | Morgan Brown | 1 | 1 | 7 | 0 | 0.04 |
| 5900 | Na Xiong | 1 | 1 | 7 | 0 | 0.04 |
| 5901 | Na Xue | 1 | 1 | 7 | 0 | 0.04 |
| 5902 | Phillip Jones | 1 | 1 | 7 | 0 | 0.04 |
| 5903 | Raymond Ponce | 1 | 1 | 7 | 0 | 0.04 |
| 5904 | Rebecca Ruiz | 1 | 1 | 7 | 0 | 0.04 |
| 5905 | Robert Anderson | 1 | 1 | 7 | 0 | 0.04 |
| 5906 | Ryan Blevins | 1 | 1 | 7 | 0 | 0.04 |
| 5907 | Samantha Snow | 1 | 1 | 7 | 0 | 0.04 |
| 5908 | Sarah Wilson | 1 | 1 | 7 | 0 | 0.04 |
| 5909 | Shannon Bennett | 1 | 1 | 7 | 0 | 0.04 |
| 5910 | Shannon Romero | 1 | 1 | 7 | 0 | 0.04 |
| 5911 | Sharon Grant | 1 | 1 | 7 | 0 | 0.04 |
| 5912 | Sharon Parrish | 1 | 1 | 7 | 0 | 0.04 |
| 5913 | Steven Cordova | 1 | 1 | 7 | 0 | 0.04 |
| 5914 | Steven Keller | 1 | 1 | 7 | 0 | 0.04 |
| 5915 | Susan Meadows | 1 | 1 | 7 | 0 | 0.04 |
| 5916 | Tao Fu | 1 | 1 | 7 | 0 | 0.04 |
| 5917 | Tao Xia | 1 | 1 | 7 | 0 | 0.04 |
| 5918 | Thomas Gray | 1 | 1 | 7 | 0 | 0.04 |
| 5919 | Valerie Matthews | 1 | 1 | 7 | 0 | 0.04 |
| 5920 | Valerie Navarro | 1 | 1 | 7 | 0 | 0.04 |
| 5921 | Xiuying Jiang | 1 | 1 | 7 | 0 | 0.04 |
| 5922 | Yang Sun | 1 | 1 | 7 | 0 | 0.04 |
| 5923 | Adam Harmon | 1 | 1 | 3 | 1 | 0.04 |
| 5924 | Angela Wolfe | 1 | 1 | 3 | 1 | 0.04 |
| 5925 | Annette Collins | 1 | 1 | 3 | 1 | 0.04 |
| 5926 | Ashley Castillo | 1 | 1 | 3 | 1 | 0.04 |
| 5927 | Bianka Tabak | 1 | 1 | 3 | 1 | 0.04 |
| 5928 | Caitlin Allen | 1 | 1 | 3 | 1 | 0.04 |
| 5929 | Calogero Zamorani | 1 | 1 | 3 | 1 | 0.04 |
| 5930 | Chelsea Mclean | 1 | 1 | 3 | 1 | 0.04 |
| 5931 | Chloe Little | 1 | 1 | 3 | 1 | 0.04 |
| 5932 | Christie Woods | 1 | 1 | 3 | 1 | 0.04 |
| 5933 | Christopher Humphrey | 1 | 1 | 3 | 1 | 0.04 |
| 5934 | Costantino Ramazzotti | 1 | 1 | 3 | 1 | 0.04 |
| 5935 | Dagmara Smorąg | 1 | 1 | 3 | 1 | 0.04 |
| 5936 | Elizabeth Hill | 1 | 1 | 3 | 1 | 0.04 |
| 5937 | Elvira Puente Alba | 1 | 1 | 3 | 1 | 0.04 |
| 5938 | Emily Campos | 1 | 1 | 3 | 1 | 0.04 |
| 5939 | Enzo Morlacchi-Grassi | 1 | 1 | 3 | 1 | 0.04 |
| 5940 | Fernanda Carocci | 1 | 1 | 3 | 1 | 0.04 |
| 5941 | Gabrielle-Susan Bousquet | 1 | 1 | 3 | 1 | 0.04 |
| 5942 | Gwendolyn Morgan | 1 | 1 | 3 | 1 | 0.04 |
| 5943 | Haley Lawson | 1 | 1 | 3 | 1 | 0.04 |
| 5944 | Haley Silva | 1 | 1 | 3 | 1 | 0.04 |
| 5945 | Henriette Pierre | 1 | 1 | 3 | 1 | 0.04 |
| 5946 | James Medina | 1 | 1 | 3 | 1 | 0.04 |
| 5947 | Janet Parks | 1 | 1 | 3 | 1 | 0.04 |
| 5948 | Jason Owen | 1 | 1 | 3 | 1 | 0.04 |
| 5949 | Jennifer Reese | 1 | 1 | 3 | 1 | 0.04 |
| 5950 | Jeremy Martinez | 1 | 1 | 3 | 1 | 0.04 |
| 5951 | Jillian Crane | 1 | 1 | 3 | 1 | 0.04 |
| 5952 | John Holt | 1 | 1 | 3 | 1 | 0.04 |
| 5953 | Jon Harris | 1 | 1 | 3 | 1 | 0.04 |
| 5954 | Jonathan Fisher | 1 | 1 | 3 | 1 | 0.04 |
| 5955 | Juliusz Kominiak | 1 | 1 | 3 | 1 | 0.04 |
| 5956 | Kenneth Maldonado | 1 | 1 | 3 | 1 | 0.04 |
| 5957 | Kevin Wells | 1 | 1 | 3 | 1 | 0.04 |
| 5958 | Kimberly Fernandez | 1 | 1 | 3 | 1 | 0.04 |
| 5959 | Klaus-Werner Gierschner | 1 | 1 | 3 | 1 | 0.04 |
| 5960 | Lara Filippelli | 1 | 1 | 3 | 1 | 0.04 |
| 5961 | Lawrence Larson | 1 | 1 | 3 | 1 | 0.04 |
| 5962 | Leslie Hinton | 1 | 1 | 3 | 1 | 0.04 |
| 5963 | Linda Burns | 1 | 1 | 3 | 1 | 0.04 |
| 5964 | Lindsay Browning | 1 | 1 | 3 | 1 | 0.04 |
| 5965 | Lindsey Broeshart | 1 | 1 | 3 | 1 | 0.04 |
| 5966 | Ludovico Sgarbi-Interminei | 1 | 1 | 3 | 1 | 0.04 |
| 5967 | Marcella Dobes | 1 | 1 | 3 | 1 | 0.04 |
| 5968 | Margherita Montanari | 1 | 1 | 3 | 1 | 0.04 |
| 5969 | Mariusz Segebahn | 1 | 1 | 3 | 1 | 0.04 |
| 5970 | Martin Jones PhD | 1 | 1 | 3 | 1 | 0.04 |
| 5971 | Matthew Best | 1 | 1 | 3 | 1 | 0.04 |
| 5972 | Maurizio Curatoli | 1 | 1 | 3 | 1 | 0.04 |
| 5973 | Megan Humphrey | 1 | 1 | 3 | 1 | 0.04 |
| 5974 | Michael Wilson | 1 | 1 | 3 | 1 | 0.04 |
| 5975 | Miss Kathleen Price | 1 | 1 | 3 | 1 | 0.04 |
| 5976 | Natalija Täsche | 1 | 1 | 3 | 1 | 0.04 |
| 5977 | Nathalie Striebitz | 1 | 1 | 3 | 1 | 0.04 |
| 5978 | Nicole Newman | 1 | 1 | 3 | 1 | 0.04 |
| 5979 | Noah Shaw | 1 | 1 | 3 | 1 | 0.04 |
| 5980 | Olaf Dymarczyk | 1 | 1 | 3 | 1 | 0.04 |
| 5981 | Orlando Garzoni | 1 | 1 | 3 | 1 | 0.04 |
| 5982 | Patrick Walsh | 1 | 1 | 3 | 1 | 0.04 |
| 5983 | Paul-Robert Bodin | 1 | 1 | 3 | 1 | 0.04 |
| 5984 | Pedro Mitschke | 1 | 1 | 3 | 1 | 0.04 |
| 5985 | Pieter van Dijk | 1 | 1 | 3 | 1 | 0.04 |
| 5986 | Rachel Hall | 1 | 1 | 3 | 1 | 0.04 |
| 5987 | Robert Stevenson | 1 | 1 | 3 | 1 | 0.04 |
| 5988 | Roger Walsh | 1 | 1 | 3 | 1 | 0.04 |
| 5989 | Rosario Alsina Saez | 1 | 1 | 3 | 1 | 0.04 |
| 5990 | Samantha Campbell | 1 | 1 | 3 | 1 | 0.04 |
| 5991 | Samuel Graham | 1 | 1 | 3 | 1 | 0.04 |
| 5992 | Sara Roman | 1 | 1 | 3 | 1 | 0.04 |
| 5993 | Sean Blackburn | 1 | 1 | 3 | 1 | 0.04 |
| 5994 | Shannon Thompson | 1 | 1 | 3 | 1 | 0.04 |
| 5995 | Sheila Acosta | 1 | 1 | 3 | 1 | 0.04 |
| 5996 | Shelby Hunt | 1 | 1 | 3 | 1 | 0.04 |
| 5997 | Sheri Hernandez | 1 | 1 | 3 | 1 | 0.04 |
| 5998 | Stephanie Bird | 1 | 1 | 3 | 1 | 0.04 |
| 5999 | Tammy Craig | 1 | 1 | 3 | 1 | 0.04 |
| 6000 | Thomas Clark | 1 | 1 | 3 | 1 | 0.04 |
| 6001 | Timothy Randolph | 1 | 1 | 3 | 1 | 0.04 |
| 6002 | Tracy Williamson | 1 | 1 | 3 | 1 | 0.04 |
| 6003 | Wesley Cain | 1 | 1 | 3 | 1 | 0.04 |
| 6004 | Wieslaw Heydrich | 1 | 1 | 3 | 1 | 0.04 |
| 6005 | William Blair | 1 | 1 | 3 | 1 | 0.04 |
| 6006 | Yong Xiang | 1 | 1 | 3 | 1 | 0.04 |
| 6007 | Zachary Rojas | 1 | 1 | 3 | 1 | 0.04 |
| 6008 | Aaron Horton | 1 | 1 | 6 | 0 | 0.04 |
| 6009 | Aarush Shukla | 1 | 1 | 6 | 0 | 0.04 |
| 6010 | Adam Hinton | 1 | 1 | 6 | 0 | 0.04 |
| 6011 | Agnolo Zaccardo-Leonetti | 1 | 1 | 6 | 0 | 0.04 |
| 6012 | Alberto Durante-Depero | 1 | 1 | 6 | 0 | 0.04 |
| 6013 | Alyssa Franklin | 1 | 1 | 6 | 0 | 0.04 |
| 6014 | Amy Conway | 1 | 1 | 6 | 0 | 0.04 |
| 6015 | Amy Thomas | 1 | 1 | 6 | 0 | 0.04 |
| 6016 | Anay Vohra | 1 | 1 | 6 | 0 | 0.04 |
| 6017 | Anja Niemeier | 1 | 1 | 6 | 0 | 0.04 |
| 6018 | Anthony Lane | 1 | 1 | 6 | 0 | 0.04 |
| 6019 | Aradhya Maharaj | 1 | 1 | 6 | 0 | 0.04 |
| 6020 | Armida Luque Mascaró | 1 | 1 | 6 | 0 | 0.04 |
| 6021 | Arnaldo Borzomì | 1 | 1 | 6 | 0 | 0.04 |
| 6022 | Ashley Logan | 1 | 1 | 6 | 0 | 0.04 |
| 6023 | Ashley Osborne | 1 | 1 | 6 | 0 | 0.04 |
| 6024 | Aurora Alboni | 1 | 1 | 6 | 0 | 0.04 |
| 6025 | Brandon Cohen | 1 | 1 | 6 | 0 | 0.04 |
| 6026 | Brandon Morales | 1 | 1 | 6 | 0 | 0.04 |
| 6027 | Brian Jones | 1 | 1 | 6 | 0 | 0.04 |
| 6028 | Briana Miller | 1 | 1 | 6 | 0 | 0.04 |
| 6029 | Calvin Cooper | 1 | 1 | 6 | 0 | 0.04 |
| 6030 | Carl Rodriguez | 1 | 1 | 6 | 0 | 0.04 |
| 6031 | Carmen Higgins | 1 | 1 | 6 | 0 | 0.04 |
| 6032 | Casey Wright | 1 | 1 | 6 | 0 | 0.04 |
| 6033 | Cemal Dowerg | 1 | 1 | 6 | 0 | 0.04 |
| 6034 | Chao Du | 1 | 1 | 6 | 0 | 0.04 |
| 6035 | Chao Ma | 1 | 1 | 6 | 0 | 0.04 |
| 6036 | Charles Marshall | 1 | 1 | 6 | 0 | 0.04 |
| 6037 | Charles Snyder | 1 | 1 | 6 | 0 | 0.04 |
| 6038 | Christina Soto | 1 | 1 | 6 | 0 | 0.04 |
| 6039 | Christopher Flores | 1 | 1 | 6 | 0 | 0.04 |
| 6040 | Christopher Jones | 1 | 1 | 6 | 0 | 0.04 |
| 6041 | Christopher Lowery | 1 | 1 | 6 | 0 | 0.04 |
| 6042 | Christopher Pham | 1 | 1 | 6 | 0 | 0.04 |
| 6043 | Concetta Davids | 1 | 1 | 6 | 0 | 0.04 |
| 6044 | Coriolano Riccati | 1 | 1 | 6 | 0 | 0.04 |
| 6045 | Craig Lewis | 1 | 1 | 6 | 0 | 0.04 |
| 6046 | Cristian Gross | 1 | 1 | 6 | 0 | 0.04 |
| 6047 | Cynthia Henson | 1 | 1 | 6 | 0 | 0.04 |
| 6048 | Danny Brooks | 1 | 1 | 6 | 0 | 0.04 |
| 6049 | David Cannon | 1 | 1 | 6 | 0 | 0.04 |
| 6050 | David Mayo | 1 | 1 | 6 | 0 | 0.04 |
| 6051 | Dawn Allen | 1 | 1 | 6 | 0 | 0.04 |
| 6052 | Dennis Bass | 1 | 1 | 6 | 0 | 0.04 |
| 6053 | Devin Wallace | 1 | 1 | 6 | 0 | 0.04 |
| 6054 | Diana White | 1 | 1 | 6 | 0 | 0.04 |
| 6055 | Diane Brooks | 1 | 1 | 6 | 0 | 0.04 |
| 6056 | Diane Segebahn | 1 | 1 | 6 | 0 | 0.04 |
| 6057 | Domenico Nette | 1 | 1 | 6 | 0 | 0.04 |
| 6058 | Doris Becker | 1 | 1 | 6 | 0 | 0.04 |
| 6059 | Ebony Acevedo | 1 | 1 | 6 | 0 | 0.04 |
| 6060 | Eddie Taylor | 1 | 1 | 6 | 0 | 0.04 |
| 6061 | Edward Parker | 1 | 1 | 6 | 0 | 0.04 |
| 6062 | Edwin Crosby | 1 | 1 | 6 | 0 | 0.04 |
| 6063 | Ela Batra | 1 | 1 | 6 | 0 | 0.04 |
| 6064 | Elizabeth Davis | 1 | 1 | 6 | 0 | 0.04 |
| 6065 | Elizabeth Spence | 1 | 1 | 6 | 0 | 0.04 |
| 6066 | Emily Gonzalez | 1 | 1 | 6 | 0 | 0.04 |
| 6067 | Eva Morosini-Procacci | 1 | 1 | 6 | 0 | 0.04 |
| 6068 | Eva-Maria Killer | 1 | 1 | 6 | 0 | 0.04 |
| 6069 | Fang Cheng | 1 | 1 | 6 | 0 | 0.04 |
| 6070 | Farhan Bava | 1 | 1 | 6 | 0 | 0.04 |
| 6071 | Franco Weitzel | 1 | 1 | 6 | 0 | 0.04 |
| 6072 | Gang Fang | 1 | 1 | 6 | 0 | 0.04 |
| 6073 | Gregory Rhodes | 1 | 1 | 6 | 0 | 0.04 |
| 6074 | Guiying Cheng | 1 | 1 | 6 | 0 | 0.04 |
| 6075 | Guiying Wang | 1 | 1 | 6 | 0 | 0.04 |
| 6076 | Gunhild Oderwald | 1 | 1 | 6 | 0 | 0.04 |
| 6077 | Hanako Suzuki | 1 | 1 | 6 | 0 | 0.04 |
| 6078 | Hansjoachim Gieß | 1 | 1 | 6 | 0 | 0.04 |
| 6079 | Heather Pollard | 1 | 1 | 6 | 0 | 0.04 |
| 6080 | Hector Smith | 1 | 1 | 6 | 0 | 0.04 |
| 6081 | Heidi Henry | 1 | 1 | 6 | 0 | 0.04 |
| 6082 | Heidi Mills | 1 | 1 | 6 | 0 | 0.04 |
| 6083 | Henriette Duval | 1 | 1 | 6 | 0 | 0.04 |
| 6084 | Herr Karl-Josef Roskoth | 1 | 1 | 6 | 0 | 0.04 |
| 6085 | Imran van Maasgouw-Schroeff | 1 | 1 | 6 | 0 | 0.04 |
| 6086 | Isis van Tours-Kathagen | 1 | 1 | 6 | 0 | 0.04 |
| 6087 | Jack Hawkins | 1 | 1 | 6 | 0 | 0.04 |
| 6088 | Jacob Garcia | 1 | 1 | 6 | 0 | 0.04 |
| 6089 | Jacob Orr | 1 | 1 | 6 | 0 | 0.04 |
| 6090 | Jacqueline Obrien | 1 | 1 | 6 | 0 | 0.04 |
| 6091 | James Cooper | 1 | 1 | 6 | 0 | 0.04 |
| 6092 | James Nolan | 1 | 1 | 6 | 0 | 0.04 |
| 6093 | Jason Mayer | 1 | 1 | 6 | 0 | 0.04 |
| 6094 | Jeffrey Lee | 1 | 1 | 6 | 0 | 0.04 |
| 6095 | Jeffrey Miller | 1 | 1 | 6 | 0 | 0.04 |
| 6096 | Jennifer Norris | 1 | 1 | 6 | 0 | 0.04 |
| 6097 | Jennifer Parker | 1 | 1 | 6 | 0 | 0.04 |
| 6098 | Jermaine York | 1 | 1 | 6 | 0 | 0.04 |
| 6099 | Jing Fu | 1 | 1 | 6 | 0 | 0.04 |
| 6100 | John Bates | 1 | 1 | 6 | 0 | 0.04 |
| 6101 | John Hopkins | 1 | 1 | 6 | 0 | 0.04 |
| 6102 | John Howe | 1 | 1 | 6 | 0 | 0.04 |
| 6103 | Jonathan Snyder | 1 | 1 | 6 | 0 | 0.04 |
| 6104 | Joseph Navarro | 1 | 1 | 6 | 0 | 0.04 |
| 6105 | Joseph Rey | 1 | 1 | 6 | 0 | 0.04 |
| 6106 | Jun Okada | 1 | 1 | 6 | 0 | 0.04 |
| 6107 | Jérôme Blanchet | 1 | 1 | 6 | 0 | 0.04 |
| 6108 | Karen White | 1 | 1 | 6 | 0 | 0.04 |
| 6109 | Kari Harvey | 1 | 1 | 6 | 0 | 0.04 |
| 6110 | Kathryn Garcia | 1 | 1 | 6 | 0 | 0.04 |
| 6111 | Kayla Holmes | 1 | 1 | 6 | 0 | 0.04 |
| 6112 | Kelly Jackson | 1 | 1 | 6 | 0 | 0.04 |
| 6113 | Kevin Clark | 1 | 1 | 6 | 0 | 0.04 |
| 6114 | Kimaya Srinivasan | 1 | 1 | 6 | 0 | 0.04 |
| 6115 | Kimberly Buchanan | 1 | 1 | 6 | 0 | 0.04 |
| 6116 | Kristina Jackson | 1 | 1 | 6 | 0 | 0.04 |
| 6117 | Lei Tian | 1 | 1 | 6 | 0 | 0.04 |
| 6118 | Letizia Agnesi-Piacentini | 1 | 1 | 6 | 0 | 0.04 |
| 6119 | Liesel Aumann | 1 | 1 | 6 | 0 | 0.04 |
| 6120 | Linda Garza | 1 | 1 | 6 | 0 | 0.04 |
| 6121 | Mandy Mendoza | 1 | 1 | 6 | 0 | 0.04 |
| 6122 | Manuel Murphy | 1 | 1 | 6 | 0 | 0.04 |
| 6123 | Marc Arroyo | 1 | 1 | 6 | 0 | 0.04 |
| 6124 | Marco Kusch | 1 | 1 | 6 | 0 | 0.04 |
| 6125 | Mark Shepard | 1 | 1 | 6 | 0 | 0.04 |
| 6126 | Martin Ramirez | 1 | 1 | 6 | 0 | 0.04 |
| 6127 | Mary Gorlitz | 1 | 1 | 6 | 0 | 0.04 |
| 6128 | Mary Harris | 1 | 1 | 6 | 0 | 0.04 |
| 6129 | Mary Lewis | 1 | 1 | 6 | 0 | 0.04 |
| 6130 | Matthew Lopez | 1 | 1 | 6 | 0 | 0.04 |
| 6131 | Matthew Mclean | 1 | 1 | 6 | 0 | 0.04 |
| 6132 | Matthew Scott | 1 | 1 | 6 | 0 | 0.04 |
| 6133 | Maurice Lacroix | 1 | 1 | 6 | 0 | 0.04 |
| 6134 | Melissa Keller | 1 | 1 | 6 | 0 | 0.04 |
| 6135 | Melissa Matthews | 1 | 1 | 6 | 0 | 0.04 |
| 6136 | Melissa Moore | 1 | 1 | 6 | 0 | 0.04 |
| 6137 | Michael Mitchell | 1 | 1 | 6 | 0 | 0.04 |
| 6138 | Michael Washington | 1 | 1 | 6 | 0 | 0.04 |
| 6139 | Micheal Collins | 1 | 1 | 6 | 0 | 0.04 |
| 6140 | Michele Johnson | 1 | 1 | 6 | 0 | 0.04 |
| 6141 | Michelle Blair | 1 | 1 | 6 | 0 | 0.04 |
| 6142 | Ming Ma | 1 | 1 | 6 | 0 | 0.04 |
| 6143 | Minoru Ikeda | 1 | 1 | 6 | 0 | 0.04 |
| 6144 | Miraan Ramachandran | 1 | 1 | 6 | 0 | 0.04 |
| 6145 | Morgan Rodriguez | 1 | 1 | 6 | 0 | 0.04 |
| 6146 | Na Fang | 1 | 1 | 6 | 0 | 0.04 |
| 6147 | Na Jiang | 1 | 1 | 6 | 0 | 0.04 |
| 6148 | Na Shen | 1 | 1 | 6 | 0 | 0.04 |
| 6149 | Na Zheng | 1 | 1 | 6 | 0 | 0.04 |
| 6150 | Nathan Carrillo | 1 | 1 | 6 | 0 | 0.04 |
| 6151 | Nichole Cruz | 1 | 1 | 6 | 0 | 0.04 |
| 6152 | Nicole Jackson | 1 | 1 | 6 | 0 | 0.04 |
| 6153 | Nicole Lamb | 1 | 1 | 6 | 0 | 0.04 |
| 6154 | Noël Loiseau | 1 | 1 | 6 | 0 | 0.04 |
| 6155 | Omar Lewis | 1 | 1 | 6 | 0 | 0.04 |
| 6156 | Onkar Kata | 1 | 1 | 6 | 0 | 0.04 |
| 6157 | Ottavio Barcella-Ritacca | 1 | 1 | 6 | 0 | 0.04 |
| 6158 | Paolo Gotthard | 1 | 1 | 6 | 0 | 0.04 |
| 6159 | Patrick Lewis | 1 | 1 | 6 | 0 | 0.04 |
| 6160 | Patrick Simon | 1 | 1 | 6 | 0 | 0.04 |
| 6161 | Paul Brown | 1 | 1 | 6 | 0 | 0.04 |
| 6162 | Pierluigi Tornatore | 1 | 1 | 6 | 0 | 0.04 |
| 6163 | Ping Wei | 1 | 1 | 6 | 0 | 0.04 |
| 6164 | Ping Zou | 1 | 1 | 6 | 0 | 0.04 |
| 6165 | Pomponio Pometta | 1 | 1 | 6 | 0 | 0.04 |
| 6166 | Pranay Sarin | 1 | 1 | 6 | 0 | 0.04 |
| 6167 | Qiang Chen | 1 | 1 | 6 | 0 | 0.04 |
| 6168 | Rachel Carroll | 1 | 1 | 6 | 0 | 0.04 |
| 6169 | Rania Deol | 1 | 1 | 6 | 0 | 0.04 |
| 6170 | Rebecca Marshall | 1 | 1 | 6 | 0 | 0.04 |
| 6171 | Renée Tanguy-Henry | 1 | 1 | 6 | 0 | 0.04 |
| 6172 | Ritvik Lanka | 1 | 1 | 6 | 0 | 0.04 |
| 6173 | Robert Santiago | 1 | 1 | 6 | 0 | 0.04 |
| 6174 | Robert Shaw | 1 | 1 | 6 | 0 | 0.04 |
| 6175 | Ryan Devan | 1 | 1 | 6 | 0 | 0.04 |
| 6176 | Ryan Roberts | 1 | 1 | 6 | 0 | 0.04 |
| 6177 | Serafina Vives-Somoza | 1 | 1 | 6 | 0 | 0.04 |
| 6178 | Shannon Allen | 1 | 1 | 6 | 0 | 0.04 |
| 6179 | Siegmar Heintze | 1 | 1 | 6 | 0 | 0.04 |
| 6180 | Silvia Baum | 1 | 1 | 6 | 0 | 0.04 |
| 6181 | Stephen Decker | 1 | 1 | 6 | 0 | 0.04 |
| 6182 | Susan Holmes | 1 | 1 | 6 | 0 | 0.04 |
| 6183 | Tami Cox | 1 | 1 | 6 | 0 | 0.04 |
| 6184 | Tammy Turner | 1 | 1 | 6 | 0 | 0.04 |
| 6185 | Tammy Williams | 1 | 1 | 6 | 0 | 0.04 |
| 6186 | Tanya Webb | 1 | 1 | 6 | 0 | 0.04 |
| 6187 | Tao Wan | 1 | 1 | 6 | 0 | 0.04 |
| 6188 | Tara Kota | 1 | 1 | 6 | 0 | 0.04 |
| 6189 | Teresa Ellis | 1 | 1 | 6 | 0 | 0.04 |
| 6190 | Thibault Ollivier | 1 | 1 | 6 | 0 | 0.04 |
| 6191 | Thomas Alvarez | 1 | 1 | 6 | 0 | 0.04 |
| 6192 | Thomas Le | 1 | 1 | 6 | 0 | 0.04 |
| 6193 | Tina Cook | 1 | 1 | 6 | 0 | 0.04 |
| 6194 | Tiya Sani | 1 | 1 | 6 | 0 | 0.04 |
| 6195 | Tracy Jones | 1 | 1 | 6 | 0 | 0.04 |
| 6196 | Tracy Wright | 1 | 1 | 6 | 0 | 0.04 |
| 6197 | Travis Hill | 1 | 1 | 6 | 0 | 0.04 |
| 6198 | Valerij Bonbach | 1 | 1 | 6 | 0 | 0.04 |
| 6199 | Valerio Carullo | 1 | 1 | 6 | 0 | 0.04 |
| 6200 | Vinnie Cole | 1 | 1 | 6 | 0 | 0.04 |
| 6201 | Walter Sexton | 1 | 1 | 6 | 0 | 0.04 |
| 6202 | Wayne Wilson | 1 | 1 | 6 | 0 | 0.04 |
| 6203 | William Sullivan | 1 | 1 | 6 | 0 | 0.04 |
| 6204 | Xiuying Gong | 1 | 1 | 6 | 0 | 0.04 |
| 6205 | Xiuying He | 1 | 1 | 6 | 0 | 0.04 |
| 6206 | Yang Hu | 1 | 1 | 6 | 0 | 0.04 |
| 6207 | Yang Jia | 1 | 1 | 6 | 0 | 0.04 |
| 6208 | Yuvraj Dar | 1 | 1 | 6 | 0 | 0.04 |
| 6209 | Élise François-Berthelot | 1 | 1 | 6 | 0 | 0.04 |
| 6210 | Andrew Juarez | 1 | 1 | 2 | 1 | 0.04 |
| 6211 | Brass Horizon Ensemble | 1 | 1 | 2 | 1 | 0.04 |
| 6212 | Brendan Hawkins | 1 | 1 | 2 | 1 | 0.04 |
| 6213 | Brittany Simon | 1 | 1 | 2 | 1 | 0.04 |
| 6214 | Bruno Majtczak | 1 | 1 | 2 | 1 | 0.04 |
| 6215 | Cezary Siedlarz | 1 | 1 | 2 | 1 | 0.04 |
| 6216 | Claus-Dieter Werner-Haering | 1 | 1 | 2 | 1 | 0.04 |
| 6217 | Elizabeth Flores | 1 | 1 | 2 | 1 | 0.04 |
| 6218 | Elizabeth Rivera | 1 | 1 | 2 | 1 | 0.04 |
| 6219 | Halil Neuschäfer | 1 | 1 | 2 | 1 | 0.04 |
| 6220 | Hannes Cichorius-Seifert | 1 | 1 | 2 | 1 | 0.04 |
| 6221 | Hélène Lecomte-Techer | 1 | 1 | 2 | 1 | 0.04 |
| 6222 | Jason Mendoza | 1 | 1 | 2 | 1 | 0.04 |
| 6223 | Jennifer Henderson | 1 | 1 | 2 | 1 | 0.04 |
| 6224 | Jeremy Bryant | 1 | 1 | 2 | 1 | 0.04 |
| 6225 | Josephine Kabus | 1 | 1 | 2 | 1 | 0.04 |
| 6226 | Kendra Spears | 1 | 1 | 2 | 1 | 0.04 |
| 6227 | Lisa Hines | 1 | 1 | 2 | 1 | 0.04 |
| 6228 | Matthew Price | 1 | 1 | 2 | 1 | 0.04 |
| 6229 | Michael Moreno | 1 | 1 | 2 | 1 | 0.04 |
| 6230 | Michael Perkins | 1 | 1 | 2 | 1 | 0.04 |
| 6231 | Midnight Terrain | 1 | 1 | 2 | 1 | 0.04 |
| 6232 | Min Song | 1 | 1 | 2 | 1 | 0.04 |
| 6233 | Neelofar Balan | 1 | 1 | 2 | 1 | 0.04 |
| 6234 | Robert Carlson | 1 | 1 | 2 | 1 | 0.04 |
| 6235 | Ronald Warner | 1 | 1 | 2 | 1 | 0.04 |
| 6236 | Samiha Aurora | 1 | 1 | 2 | 1 | 0.04 |
| 6237 | Susan Garcia | 1 | 1 | 2 | 1 | 0.04 |
| 6238 | Violetta Peukert | 1 | 1 | 2 | 1 | 0.04 |
| 6239 | Wei Hao | 1 | 1 | 2 | 1 | 0.04 |
| 6240 | Aarav Balan | 1 | 1 | 5 | 0 | 0.04 |
| 6241 | Adam Reid | 1 | 1 | 5 | 0 | 0.04 |
| 6242 | Advik Shroff | 1 | 1 | 5 | 0 | 0.04 |
| 6243 | Alexis Vincent | 1 | 1 | 5 | 0 | 0.04 |
| 6244 | Alicia Rice | 1 | 1 | 5 | 0 | 0.04 |
| 6245 | Allison Barnes | 1 | 1 | 5 | 0 | 0.04 |
| 6246 | Amanda Black | 1 | 1 | 5 | 0 | 0.04 |
| 6247 | Amanda English | 1 | 1 | 5 | 0 | 0.04 |
| 6248 | Amanda Moore | 1 | 1 | 5 | 0 | 0.04 |
| 6249 | Amber Smith | 1 | 1 | 5 | 0 | 0.04 |
| 6250 | Amy Rodriguez | 1 | 1 | 5 | 0 | 0.04 |
| 6251 | Ana Collins | 1 | 1 | 5 | 0 | 0.04 |
| 6252 | Andrea Duncan | 1 | 1 | 5 | 0 | 0.04 |
| 6253 | Andrew Montes | 1 | 1 | 5 | 0 | 0.04 |
| 6254 | Angela Black | 1 | 1 | 5 | 0 | 0.04 |
| 6255 | Angela Rios | 1 | 1 | 5 | 0 | 0.04 |
| 6256 | Anita Szałata | 1 | 1 | 5 | 0 | 0.04 |
| 6257 | Annelise Heidrich | 1 | 1 | 5 | 0 | 0.04 |
| 6258 | Anthony Adams | 1 | 1 | 5 | 0 | 0.04 |
| 6259 | Anthony Bailey | 1 | 1 | 5 | 0 | 0.04 |
| 6260 | Anthony Wheeler | 1 | 1 | 5 | 0 | 0.04 |
| 6261 | Arnav Saran | 1 | 1 | 5 | 0 | 0.04 |
| 6262 | Aroa Coca | 1 | 1 | 5 | 0 | 0.04 |
| 6263 | Arthur Lewis | 1 | 1 | 5 | 0 | 0.04 |
| 6264 | Ashley Hernandez | 1 | 1 | 5 | 0 | 0.04 |
| 6265 | Ashley Moore | 1 | 1 | 5 | 0 | 0.04 |
| 6266 | Auguste Perrin | 1 | 1 | 5 | 0 | 0.04 |
| 6267 | Bekir Ladeck | 1 | 1 | 5 | 0 | 0.04 |
| 6268 | Ben Ponci | 1 | 1 | 5 | 0 | 0.04 |
| 6269 | Benjamin Leon | 1 | 1 | 5 | 0 | 0.04 |
| 6270 | Beverly Johnson | 1 | 1 | 5 | 0 | 0.04 |
| 6271 | Bianca Ward | 1 | 1 | 5 | 0 | 0.04 |
| 6272 | Bradley Small | 1 | 1 | 5 | 0 | 0.04 |
| 6273 | Brandi Price | 1 | 1 | 5 | 0 | 0.04 |
| 6274 | Brian Le | 1 | 1 | 5 | 0 | 0.04 |
| 6275 | Briana Johnson | 1 | 1 | 5 | 0 | 0.04 |
| 6276 | Brianna Williams | 1 | 1 | 5 | 0 | 0.04 |
| 6277 | Brittany Wright | 1 | 1 | 5 | 0 | 0.04 |
| 6278 | Camillo Liguori-Pistoletto | 1 | 1 | 5 | 0 | 0.04 |
| 6279 | Carl Serrano | 1 | 1 | 5 | 0 | 0.04 |
| 6280 | Carlos Anderson | 1 | 1 | 5 | 0 | 0.04 |
| 6281 | Carlos Davis | 1 | 1 | 5 | 0 | 0.04 |
| 6282 | Carrie Webb | 1 | 1 | 5 | 0 | 0.04 |
| 6283 | Cassandra Hernandez | 1 | 1 | 5 | 0 | 0.04 |
| 6284 | Cathrin Bruder | 1 | 1 | 5 | 0 | 0.04 |
| 6285 | Chao Kang | 1 | 1 | 5 | 0 | 0.04 |
| 6286 | Chao Xia | 1 | 1 | 5 | 0 | 0.04 |
| 6287 | Charles Horton | 1 | 1 | 5 | 0 | 0.04 |
| 6288 | Christine Anderson | 1 | 1 | 5 | 0 | 0.04 |
| 6289 | Christopher Clark | 1 | 1 | 5 | 0 | 0.04 |
| 6290 | Christopher Fox | 1 | 1 | 5 | 0 | 0.04 |
| 6291 | Christopher Richards | 1 | 1 | 5 | 0 | 0.04 |
| 6292 | Connie Turner | 1 | 1 | 5 | 0 | 0.04 |
| 6293 | Corrado Chinnici-Ferrabosco | 1 | 1 | 5 | 0 | 0.04 |
| 6294 | Cory Carr | 1 | 1 | 5 | 0 | 0.04 |
| 6295 | Cynthia Lewis | 1 | 1 | 5 | 0 | 0.04 |
| 6296 | Cynthia Nash | 1 | 1 | 5 | 0 | 0.04 |
| 6297 | Daniel Campbell | 1 | 1 | 5 | 0 | 0.04 |
| 6298 | Daria Ceravolo | 1 | 1 | 5 | 0 | 0.04 |
| 6299 | Darko Kambs | 1 | 1 | 5 | 0 | 0.04 |
| 6300 | Dave Miller | 1 | 1 | 5 | 0 | 0.04 |
| 6301 | David Hebert | 1 | 1 | 5 | 0 | 0.04 |
| 6302 | Denise Moody | 1 | 1 | 5 | 0 | 0.04 |
| 6303 | Denise Price | 1 | 1 | 5 | 0 | 0.04 |
| 6304 | Derek Baxter | 1 | 1 | 5 | 0 | 0.04 |
| 6305 | Dharmajan Lad | 1 | 1 | 5 | 0 | 0.04 |
| 6306 | Donna Christensen | 1 | 1 | 5 | 0 | 0.04 |
| 6307 | Douglas Nguyen | 1 | 1 | 5 | 0 | 0.04 |
| 6308 | Elizabeth Lin | 1 | 1 | 5 | 0 | 0.04 |
| 6309 | Emily Merritt | 1 | 1 | 5 | 0 | 0.04 |
| 6310 | Emma Venditti-Brugnaro | 1 | 1 | 5 | 0 | 0.04 |
| 6311 | Eric Sanchez | 1 | 1 | 5 | 0 | 0.04 |
| 6312 | Erica Poole | 1 | 1 | 5 | 0 | 0.04 |
| 6313 | Eva Ray | 1 | 1 | 5 | 0 | 0.04 |
| 6314 | Evan Solis | 1 | 1 | 5 | 0 | 0.04 |
| 6315 | Evangelista Muti | 1 | 1 | 5 | 0 | 0.04 |
| 6316 | Fang Peng | 1 | 1 | 5 | 0 | 0.04 |
| 6317 | Fito Pacheco León | 1 | 1 | 5 | 0 | 0.04 |
| 6318 | Fractured Mirrors | 1 | 1 | 5 | 0 | 0.04 |
| 6319 | Frau Evelyn Schmiedt | 1 | 1 | 5 | 0 | 0.04 |
| 6320 | Fryderyk Deptuch | 1 | 1 | 5 | 0 | 0.04 |
| 6321 | Gary Edwards | 1 | 1 | 5 | 0 | 0.04 |
| 6322 | Gatik Gandhi | 1 | 1 | 5 | 0 | 0.04 |
| 6323 | Gatik Thaker | 1 | 1 | 5 | 0 | 0.04 |
| 6324 | George Russell | 1 | 1 | 5 | 0 | 0.04 |
| 6325 | Gerhardt Jäkel | 1 | 1 | 5 | 0 | 0.04 |
| 6326 | Gerold Boucsein-Oestrovsky | 1 | 1 | 5 | 0 | 0.04 |
| 6327 | Geronimo Morpurgo | 1 | 1 | 5 | 0 | 0.04 |
| 6328 | Gokul Dhaliwal | 1 | 1 | 5 | 0 | 0.04 |
| 6329 | Gregory Romero | 1 | 1 | 5 | 0 | 0.04 |
| 6330 | Hannah Wilkinson | 1 | 1 | 5 | 0 | 0.04 |
| 6331 | Harri Oderwald | 1 | 1 | 5 | 0 | 0.04 |
| 6332 | Hector Jones | 1 | 1 | 5 | 0 | 0.04 |
| 6333 | Heinz-Dieter Pruschke | 1 | 1 | 5 | 0 | 0.04 |
| 6334 | Henry Norris | 1 | 1 | 5 | 0 | 0.04 |
| 6335 | Ibán Salazar | 1 | 1 | 5 | 0 | 0.04 |
| 6336 | Indrajit Halder | 1 | 1 | 5 | 0 | 0.04 |
| 6337 | Isidor Hethur | 1 | 1 | 5 | 0 | 0.04 |
| 6338 | Ivo Cannizzaro | 1 | 1 | 5 | 0 | 0.04 |
| 6339 | James Perry | 1 | 1 | 5 | 0 | 0.04 |
| 6340 | James Rice | 1 | 1 | 5 | 0 | 0.04 |
| 6341 | Jamie Walker | 1 | 1 | 5 | 0 | 0.04 |
| 6342 | Jaroslava Hrubá | 1 | 1 | 5 | 0 | 0.04 |
| 6343 | Jasmin Rogner | 1 | 1 | 5 | 0 | 0.04 |
| 6344 | Jason Hendricks | 1 | 1 | 5 | 0 | 0.04 |
| 6345 | Jayan Chawla | 1 | 1 | 5 | 0 | 0.04 |
| 6346 | Jeffery Mitchell | 1 | 1 | 5 | 0 | 0.04 |
| 6347 | Jennifer Meadows | 1 | 1 | 5 | 0 | 0.04 |
| 6348 | Jennifer Olson | 1 | 1 | 5 | 0 | 0.04 |
| 6349 | Jessica Fry | 1 | 1 | 5 | 0 | 0.04 |
| 6350 | Jie Bai | 1 | 1 | 5 | 0 | 0.04 |
| 6351 | Jie Tang | 1 | 1 | 5 | 0 | 0.04 |
| 6352 | Jindřich Zeman | 1 | 1 | 5 | 0 | 0.04 |
| 6353 | Jing Xiong | 1 | 1 | 5 | 0 | 0.04 |
| 6354 | Jodi Morgan | 1 | 1 | 5 | 0 | 0.04 |
| 6355 | John Cortez | 1 | 1 | 5 | 0 | 0.04 |
| 6356 | John Kemp | 1 | 1 | 5 | 0 | 0.04 |
| 6357 | John Wheeler | 1 | 1 | 5 | 0 | 0.04 |
| 6358 | Joseph Cole | 1 | 1 | 5 | 0 | 0.04 |
| 6359 | Joseph Walton | 1 | 1 | 5 | 0 | 0.04 |
| 6360 | Joshua Best | 1 | 1 | 5 | 0 | 0.04 |
| 6361 | Jun Lu | 1 | 1 | 5 | 0 | 0.04 |
| 6362 | Jun Ren | 1 | 1 | 5 | 0 | 0.04 |
| 6363 | Jun Sun | 1 | 1 | 5 | 0 | 0.04 |
| 6364 | Kaira Saxena | 1 | 1 | 5 | 0 | 0.04 |
| 6365 | Kana Ito | 1 | 1 | 5 | 0 | 0.04 |
| 6366 | Karen Sanchez | 1 | 1 | 5 | 0 | 0.04 |
| 6367 | Karla Säuberlich-Reichmann | 1 | 1 | 5 | 0 | 0.04 |
| 6368 | Katelyn Chavez | 1 | 1 | 5 | 0 | 0.04 |
| 6369 | Katherine Dodson | 1 | 1 | 5 | 0 | 0.04 |
| 6370 | Katherine Flores | 1 | 1 | 5 | 0 | 0.04 |
| 6371 | Katherine Gutierrez | 1 | 1 | 5 | 0 | 0.04 |
| 6372 | Katherine Ortega | 1 | 1 | 5 | 0 | 0.04 |
| 6373 | Katherine Smith | 1 | 1 | 5 | 0 | 0.04 |
| 6374 | Kathy Castro | 1 | 1 | 5 | 0 | 0.04 |
| 6375 | Katie Bryant | 1 | 1 | 5 | 0 | 0.04 |
| 6376 | Kelli Martinez | 1 | 1 | 5 | 0 | 0.04 |
| 6377 | Kelly Boyd | 1 | 1 | 5 | 0 | 0.04 |
| 6378 | Kelly Dickson | 1 | 1 | 5 | 0 | 0.04 |
| 6379 | Kick van Geffen | 1 | 1 | 5 | 0 | 0.04 |
| 6380 | Kimberly House | 1 | 1 | 5 | 0 | 0.04 |
| 6381 | Krystyna Szklarek | 1 | 1 | 5 | 0 | 0.04 |
| 6382 | Kunigunda Losekann | 1 | 1 | 5 | 0 | 0.04 |
| 6383 | Lando Bulzoni | 1 | 1 | 5 | 0 | 0.04 |
| 6384 | Larry Patel | 1 | 1 | 5 | 0 | 0.04 |
| 6385 | Lauretta Vittadello | 1 | 1 | 5 | 0 | 0.04 |
| 6386 | Lei Ding | 1 | 1 | 5 | 0 | 0.04 |
| 6387 | Lei Han | 1 | 1 | 5 | 0 | 0.04 |
| 6388 | Lei Mo | 1 | 1 | 5 | 0 | 0.04 |
| 6389 | Lei Ye | 1 | 1 | 5 | 0 | 0.04 |
| 6390 | Leonard Schwital | 1 | 1 | 5 | 0 | 0.04 |
| 6391 | Li Qiao | 1 | 1 | 5 | 0 | 0.04 |
| 6392 | Liam de Vrome | 1 | 1 | 5 | 0 | 0.04 |
| 6393 | Liesbeth Köhler | 1 | 1 | 5 | 0 | 0.04 |
| 6394 | Lindsey Simpson | 1 | 1 | 5 | 0 | 0.04 |
| 6395 | Lisa Payne | 1 | 1 | 5 | 0 | 0.04 |
| 6396 | Lisa Pennington | 1 | 1 | 5 | 0 | 0.04 |
| 6397 | Liza Mahieu-Groenestein | 1 | 1 | 5 | 0 | 0.04 |
| 6398 | Liza Rijcken | 1 | 1 | 5 | 0 | 0.04 |
| 6399 | Lucia Ceci | 1 | 1 | 5 | 0 | 0.04 |
| 6400 | Mackenzie Compton | 1 | 1 | 5 | 0 | 0.04 |
| 6401 | Madhup Banerjee | 1 | 1 | 5 | 0 | 0.04 |
| 6402 | Magdalene Rust | 1 | 1 | 5 | 0 | 0.04 |
| 6403 | Mannat Chad | 1 | 1 | 5 | 0 | 0.04 |
| 6404 | Maria Romero | 1 | 1 | 5 | 0 | 0.04 |
| 6405 | Marietta Kraushaar | 1 | 1 | 5 | 0 | 0.04 |
| 6406 | Mark Martinez | 1 | 1 | 5 | 0 | 0.04 |
| 6407 | Mark Mueller | 1 | 1 | 5 | 0 | 0.04 |
| 6408 | Mark Nunez | 1 | 1 | 5 | 0 | 0.04 |
| 6409 | Mathias Tröst | 1 | 1 | 5 | 0 | 0.04 |
| 6410 | Mathilde Ribeiro | 1 | 1 | 5 | 0 | 0.04 |
| 6411 | Matthew Burton | 1 | 1 | 5 | 0 | 0.04 |
| 6412 | Matthew Collins | 1 | 1 | 5 | 0 | 0.04 |
| 6413 | Matthew Moyer | 1 | 1 | 5 | 0 | 0.04 |
| 6414 | Melanie Ballard | 1 | 1 | 5 | 0 | 0.04 |
| 6415 | Michael Martinez | 1 | 1 | 5 | 0 | 0.04 |
| 6416 | Michael Patton | 1 | 1 | 5 | 0 | 0.04 |
| 6417 | Michael Pineda | 1 | 1 | 5 | 0 | 0.04 |
| 6418 | Michelle Aguirre | 1 | 1 | 5 | 0 | 0.04 |
| 6419 | Miki Kondo | 1 | 1 | 5 | 0 | 0.04 |
| 6420 | Miloš Horváth | 1 | 1 | 5 | 0 | 0.04 |
| 6421 | Mitchell Ross | 1 | 1 | 5 | 0 | 0.04 |
| 6422 | Na Du | 1 | 1 | 5 | 0 | 0.04 |
| 6423 | Na Lei | 1 | 1 | 5 | 0 | 0.04 |
| 6424 | Natalie Hernandez | 1 | 1 | 5 | 0 | 0.04 |
| 6425 | Natalie Wood | 1 | 1 | 5 | 0 | 0.04 |
| 6426 | Nermin Förster | 1 | 1 | 5 | 0 | 0.04 |
| 6427 | Nichole Dean | 1 | 1 | 5 | 0 | 0.04 |
| 6428 | Nico Casalodi | 1 | 1 | 5 | 0 | 0.04 |
| 6429 | Nicole Thomas | 1 | 1 | 5 | 0 | 0.04 |
| 6430 | Ojas Ramakrishnan | 1 | 1 | 5 | 0 | 0.04 |
| 6431 | Orazio Curatoli | 1 | 1 | 5 | 0 | 0.04 |
| 6432 | Paige Mitchell | 1 | 1 | 5 | 0 | 0.04 |
| 6433 | Pamela Reynolds | 1 | 1 | 5 | 0 | 0.04 |
| 6434 | Peter Arnold | 1 | 1 | 5 | 0 | 0.04 |
| 6435 | Peter Hughes | 1 | 1 | 5 | 0 | 0.04 |
| 6436 | Piermaria Bevilacqua-Altera | 1 | 1 | 5 | 0 | 0.04 |
| 6437 | Pihu Sunder | 1 | 1 | 5 | 0 | 0.04 |
| 6438 | Ping Qian | 1 | 1 | 5 | 0 | 0.04 |
| 6439 | Priyansh Bahl | 1 | 1 | 5 | 0 | 0.04 |
| 6440 | Puccio Farnese | 1 | 1 | 5 | 0 | 0.04 |
| 6441 | Qiang Qiu | 1 | 1 | 5 | 0 | 0.04 |
| 6442 | Qiang Yi | 1 | 1 | 5 | 0 | 0.04 |
| 6443 | Rachel Ford | 1 | 1 | 5 | 0 | 0.04 |
| 6444 | Radomír Hruška | 1 | 1 | 5 | 0 | 0.04 |
| 6445 | Rebecca Thompson | 1 | 1 | 5 | 0 | 0.04 |
| 6446 | Renee Matthews | 1 | 1 | 5 | 0 | 0.04 |
| 6447 | Richard Cook | 1 | 1 | 5 | 0 | 0.04 |
| 6448 | Robert White | 1 | 1 | 5 | 0 | 0.04 |
| 6449 | Robert Williams | 1 | 1 | 5 | 0 | 0.04 |
| 6450 | Robin Miller | 1 | 1 | 5 | 0 | 0.04 |
| 6451 | Roger Morgan | 1 | 1 | 5 | 0 | 0.04 |
| 6452 | Rolf Pölitz | 1 | 1 | 5 | 0 | 0.04 |
| 6453 | Ronald Johnson | 1 | 1 | 5 | 0 | 0.04 |
| 6454 | Ronald Santos | 1 | 1 | 5 | 0 | 0.04 |
| 6455 | Rosmarie Losekann | 1 | 1 | 5 | 0 | 0.04 |
| 6456 | Roy Dominguez | 1 | 1 | 5 | 0 | 0.04 |
| 6457 | Ryan Conley | 1 | 1 | 5 | 0 | 0.04 |
| 6458 | Ryan van 't Houteveen-Luboch | 1 | 1 | 5 | 0 | 0.04 |
| 6459 | Sara Ramirez | 1 | 1 | 5 | 0 | 0.04 |
| 6460 | Sarah Brown | 1 | 1 | 5 | 0 | 0.04 |
| 6461 | Sarah Collins | 1 | 1 | 5 | 0 | 0.04 |
| 6462 | Scott Daniel | 1 | 1 | 5 | 0 | 0.04 |
| 6463 | Severo Gimenez Ródenas | 1 | 1 | 5 | 0 | 0.04 |
| 6464 | Shalv Sarin | 1 | 1 | 5 | 0 | 0.04 |
| 6465 | Shanaya Dave | 1 | 1 | 5 | 0 | 0.04 |
| 6466 | Sharon Holland | 1 | 1 | 5 | 0 | 0.04 |
| 6467 | Shayak Sen | 1 | 1 | 5 | 0 | 0.04 |
| 6468 | Sherry Flores | 1 | 1 | 5 | 0 | 0.04 |
| 6469 | Shray Ranganathan | 1 | 1 | 5 | 0 | 0.04 |
| 6470 | Sierra Gibson | 1 | 1 | 5 | 0 | 0.04 |
| 6471 | Silva Speer | 1 | 1 | 5 | 0 | 0.04 |
| 6472 | Stella Fusani | 1 | 1 | 5 | 0 | 0.04 |
| 6473 | Stephen Pope | 1 | 1 | 5 | 0 | 0.04 |
| 6474 | Sue May | 1 | 1 | 5 | 0 | 0.04 |
| 6475 | Susan Briggs | 1 | 1 | 5 | 0 | 0.04 |
| 6476 | Susan Evans | 1 | 1 | 5 | 0 | 0.04 |
| 6477 | Suzanne Bonilla | 1 | 1 | 5 | 0 | 0.04 |
| 6478 | Tao Cao | 1 | 1 | 5 | 0 | 0.04 |
| 6479 | Tao Liang | 1 | 1 | 5 | 0 | 0.04 |
| 6480 | Tao Wang | 1 | 1 | 5 | 0 | 0.04 |
| 6481 | Tara Basu | 1 | 1 | 5 | 0 | 0.04 |
| 6482 | Tarini Bora | 1 | 1 | 5 | 0 | 0.04 |
| 6483 | Taylor Miller | 1 | 1 | 5 | 0 | 0.04 |
| 6484 | Taylor Perry | 1 | 1 | 5 | 0 | 0.04 |
| 6485 | Thierry Fernandez Le Bègue | 1 | 1 | 5 | 0 | 0.04 |
| 6486 | Tiffany Kelly | 1 | 1 | 5 | 0 | 0.04 |
| 6487 | Tracy Warner | 1 | 1 | 5 | 0 | 0.04 |
| 6488 | Tracy Warren | 1 | 1 | 5 | 0 | 0.04 |
| 6489 | Trevor Freeman | 1 | 1 | 5 | 0 | 0.04 |
| 6490 | Tyler Lee | 1 | 1 | 5 | 0 | 0.04 |
| 6491 | Tyler Martinez | 1 | 1 | 5 | 0 | 0.04 |
| 6492 | Ugolino Bettin | 1 | 1 | 5 | 0 | 0.04 |
| 6493 | Victoire Roger-Noël | 1 | 1 | 5 | 0 | 0.04 |
| 6494 | Victor Scott | 1 | 1 | 5 | 0 | 0.04 |
| 6495 | Virginia Stuart | 1 | 1 | 5 | 0 | 0.04 |
| 6496 | Vlastimil Pokorný | 1 | 1 | 5 | 0 | 0.04 |
| 6497 | Wanda Fuller | 1 | 1 | 5 | 0 | 0.04 |
| 6498 | Wei Fang | 1 | 1 | 5 | 0 | 0.04 |
| 6499 | Wei Fu | 1 | 1 | 5 | 0 | 0.04 |
| 6500 | Wei Xiang | 1 | 1 | 5 | 0 | 0.04 |
| 6501 | Wendy Ayala | 1 | 1 | 5 | 0 | 0.04 |
| 6502 | Whitney Tucker | 1 | 1 | 5 | 0 | 0.04 |
| 6503 | Whitney Williams | 1 | 1 | 5 | 0 | 0.04 |
| 6504 | William Donovan | 1 | 1 | 5 | 0 | 0.04 |
| 6505 | Xiuying Liu | 1 | 1 | 5 | 0 | 0.04 |
| 6506 | Xiuying Shao | 1 | 1 | 5 | 0 | 0.04 |
| 6507 | Xiuying Wu | 1 | 1 | 5 | 0 | 0.04 |
| 6508 | Yan Huang | 1 | 1 | 5 | 0 | 0.04 |
| 6509 | Yang Wang | 1 | 1 | 5 | 0 | 0.04 |
| 6510 | Yolanda Hernandez | 1 | 1 | 5 | 0 | 0.04 |
| 6511 | Yong Cai | 1 | 1 | 5 | 0 | 0.04 |
| 6512 | Yong Peng | 1 | 1 | 5 | 0 | 0.04 |
| 6513 | Zachary Ellis | 1 | 1 | 5 | 0 | 0.04 |
| 6514 | Zaira Peano-Castelli | 1 | 1 | 5 | 0 | 0.04 |
| 6515 | Zaira Verga-Cannizzaro | 1 | 1 | 5 | 0 | 0.04 |
| 6516 | Zeeshan Manda | 1 | 1 | 5 | 0 | 0.04 |
| 6517 | Deborah Hayes | 1 | 0 | 11 | 3 | 0.04 |
| 6518 | Pihu Chowdhury | 1 | 0 | 11 | 3 | 0.04 |
| 6519 | Stephanie Wilson | 1 | 0 | 11 | 3 | 0.04 |
| 6520 | Amber Ward | 1 | 1 | 1 | 1 | 0.04 |
| 6521 | Anay Dey | 1 | 1 | 1 | 1 | 0.04 |
| 6522 | Anna Maria Michel | 1 | 1 | 1 | 1 | 0.04 |
| 6523 | Aurora Calarco | 1 | 1 | 1 | 1 | 0.04 |
| 6524 | Daniel Bluszcz | 1 | 1 | 1 | 1 | 0.04 |
| 6525 | Janina Worach | 1 | 1 | 1 | 1 | 0.04 |
| 6526 | Joshua Taylor | 1 | 1 | 1 | 1 | 0.04 |
| 6527 | Shannon Harvey | 1 | 1 | 1 | 1 | 0.04 |
| 6528 | Veronica Burns | 1 | 1 | 1 | 1 | 0.04 |
| 6529 | Stephanie Roberts | 1 | 0 | 14 | 2 | 0.04 |
| 6530 | Juno Ray | 2 | 0 | 5 | 0 | 0.04 |
| 6531 | Savannah Teal | 2 | 0 | 5 | 0 | 0.04 |
| 6532 | Aaron Carter | 1 | 1 | 4 | 0 | 0.04 |
| 6533 | Abigail Hawkins | 1 | 1 | 4 | 0 | 0.04 |
| 6534 | Abigaíl del Franch | 1 | 1 | 4 | 0 | 0.04 |
| 6535 | Abril Serna | 1 | 1 | 4 | 0 | 0.04 |
| 6536 | Adele Curatoli | 1 | 1 | 4 | 0 | 0.04 |
| 6537 | Adira Bhagat | 1 | 1 | 4 | 0 | 0.04 |
| 6538 | Adrian Blevins | 1 | 1 | 4 | 0 | 0.04 |
| 6539 | Adrien Gaudin | 1 | 1 | 4 | 0 | 0.04 |
| 6540 | Adrienne Godard | 1 | 1 | 4 | 0 | 0.04 |
| 6541 | Alain du Vaillant | 1 | 1 | 4 | 0 | 0.04 |
| 6542 | Alejandro Baker | 1 | 1 | 4 | 0 | 0.04 |
| 6543 | Alex Schwartz | 1 | 1 | 4 | 0 | 0.04 |
| 6544 | Alex Smith | 1 | 1 | 4 | 0 | 0.04 |
| 6545 | Alexander Curry Jr. | 1 | 1 | 4 | 0 | 0.04 |
| 6546 | Alexandra Montes | 1 | 1 | 4 | 0 | 0.04 |
| 6547 | Alicia Jordan | 1 | 1 | 4 | 0 | 0.04 |
| 6548 | Allison Curtis | 1 | 1 | 4 | 0 | 0.04 |
| 6549 | Allison Marshall | 1 | 1 | 4 | 0 | 0.04 |
| 6550 | Alyssa Adams | 1 | 1 | 4 | 0 | 0.04 |
| 6551 | Amanda Baker | 1 | 1 | 4 | 0 | 0.04 |
| 6552 | Amanda Coleman | 1 | 1 | 4 | 0 | 0.04 |
| 6553 | Amanda Hardy | 1 | 1 | 4 | 0 | 0.04 |
| 6554 | Amber Sanders | 1 | 1 | 4 | 0 | 0.04 |
| 6555 | Amy Carroll | 1 | 1 | 4 | 0 | 0.04 |
| 6556 | Amy Johnston | 1 | 1 | 4 | 0 | 0.04 |
| 6557 | Anastasios Hölzenbecher-Henschel | 1 | 1 | 4 | 0 | 0.04 |
| 6558 | Anay Boase | 1 | 1 | 4 | 0 | 0.04 |
| 6559 | Anaïs Blanchard | 1 | 1 | 4 | 0 | 0.04 |
| 6560 | Andrew Cruz | 1 | 1 | 4 | 0 | 0.04 |
| 6561 | Andrew Lee | 1 | 1 | 4 | 0 | 0.04 |
| 6562 | Andy Eigenwillig | 1 | 1 | 4 | 0 | 0.04 |
| 6563 | Aneta Mies-Fritsch | 1 | 1 | 4 | 0 | 0.04 |
| 6564 | Anica Baum | 1 | 1 | 4 | 0 | 0.04 |
| 6565 | Anthony Burns | 1 | 1 | 4 | 0 | 0.04 |
| 6566 | Anthony Hamilton | 1 | 1 | 4 | 0 | 0.04 |
| 6567 | Anthony Padilla | 1 | 1 | 4 | 0 | 0.04 |
| 6568 | Anthony Silva | 1 | 1 | 4 | 0 | 0.04 |
| 6569 | Antonia Balotelli | 1 | 1 | 4 | 0 | 0.04 |
| 6570 | Ashlee White | 1 | 1 | 4 | 0 | 0.04 |
| 6571 | Beatrix Mende | 1 | 1 | 4 | 0 | 0.04 |
| 6572 | Benjamin Chen | 1 | 1 | 4 | 0 | 0.04 |
| 6573 | Benjamin Valencia | 1 | 1 | 4 | 0 | 0.04 |
| 6574 | Bernardita Marisol Marqués Sosa | 1 | 1 | 4 | 0 | 0.04 |
| 6575 | Beverly Pham | 1 | 1 | 4 | 0 | 0.04 |
| 6576 | Bobby Walters | 1 | 1 | 4 | 0 | 0.04 |
| 6577 | Brandon Dillon | 1 | 1 | 4 | 0 | 0.04 |
| 6578 | Brandon Flores | 1 | 1 | 4 | 0 | 0.04 |
| 6579 | Brandon Marshall | 1 | 1 | 4 | 0 | 0.04 |
| 6580 | Brent White | 1 | 1 | 4 | 0 | 0.04 |
| 6581 | Brett Mcdonald | 1 | 1 | 4 | 0 | 0.04 |
| 6582 | Brian Garrett | 1 | 1 | 4 | 0 | 0.04 |
| 6583 | Brian Hall | 1 | 1 | 4 | 0 | 0.04 |
| 6584 | Brian Hamilton | 1 | 1 | 4 | 0 | 0.04 |
| 6585 | Brian Mcbride | 1 | 1 | 4 | 0 | 0.04 |
| 6586 | Brian Pratt | 1 | 1 | 4 | 0 | 0.04 |
| 6587 | Brianna Gray | 1 | 1 | 4 | 0 | 0.04 |
| 6588 | Brittany Oliver | 1 | 1 | 4 | 0 | 0.04 |
| 6589 | Brittney Rivera | 1 | 1 | 4 | 0 | 0.04 |
| 6590 | Brooke Robinson | 1 | 1 | 4 | 0 | 0.04 |
| 6591 | Bruce Young | 1 | 1 | 4 | 0 | 0.04 |
| 6592 | Bryan Laffray-Recers | 1 | 1 | 4 | 0 | 0.04 |
| 6593 | Caleb Hunter | 1 | 1 | 4 | 0 | 0.04 |
| 6594 | Calvin Quinn | 1 | 1 | 4 | 0 | 0.04 |
| 6595 | Carly Luna | 1 | 1 | 4 | 0 | 0.04 |
| 6596 | Carol Wallace | 1 | 1 | 4 | 0 | 0.04 |
| 6597 | Caroline Lewis | 1 | 1 | 4 | 0 | 0.04 |
| 6598 | Caroline Williams | 1 | 1 | 4 | 0 | 0.04 |
| 6599 | Carolyn Ramos | 1 | 1 | 4 | 0 | 0.04 |
| 6600 | Carrie Griffin | 1 | 1 | 4 | 0 | 0.04 |
| 6601 | Casey Perez | 1 | 1 | 4 | 0 | 0.04 |
| 6602 | Cathy Oconnor | 1 | 1 | 4 | 0 | 0.04 |
| 6603 | Cemal Boucsein | 1 | 1 | 4 | 0 | 0.04 |
| 6604 | Chad Gibson | 1 | 1 | 4 | 0 | 0.04 |
| 6605 | Chao Long | 1 | 1 | 4 | 0 | 0.04 |
| 6606 | Chao Lu | 1 | 1 | 4 | 0 | 0.04 |
| 6607 | Charles White | 1 | 1 | 4 | 0 | 0.04 |
| 6608 | Charlotte Escobar | 1 | 1 | 4 | 0 | 0.04 |
| 6609 | Chelsea Harris | 1 | 1 | 4 | 0 | 0.04 |
| 6610 | Chelsea Liu | 1 | 1 | 4 | 0 | 0.04 |
| 6611 | Cheryl Miller | 1 | 1 | 4 | 0 | 0.04 |
| 6612 | Cheryl Peterson | 1 | 1 | 4 | 0 | 0.04 |
| 6613 | Chris Ward | 1 | 1 | 4 | 0 | 0.04 |
| 6614 | Christy Hodges | 1 | 1 | 4 | 0 | 0.04 |
| 6615 | Cilli Trommler | 1 | 1 | 4 | 0 | 0.04 |
| 6616 | Cindy Moore | 1 | 1 | 4 | 0 | 0.04 |
| 6617 | Cindy Zamora | 1 | 1 | 4 | 0 | 0.04 |
| 6618 | Clara Weitzel | 1 | 1 | 4 | 0 | 0.04 |
| 6619 | Claudine Martin | 1 | 1 | 4 | 0 | 0.04 |
| 6620 | Colleen Sandoval | 1 | 1 | 4 | 0 | 0.04 |
| 6621 | Cynthia Moore | 1 | 1 | 4 | 0 | 0.04 |
| 6622 | Célina Collin de la Chauveau | 1 | 1 | 4 | 0 | 0.04 |
| 6623 | Dale Suarez | 1 | 1 | 4 | 0 | 0.04 |
| 6624 | Dana Green | 1 | 1 | 4 | 0 | 0.04 |
| 6625 | Daniel Kent | 1 | 1 | 4 | 0 | 0.04 |
| 6626 | David Castaneda | 1 | 1 | 4 | 0 | 0.04 |
| 6627 | David Chandler | 1 | 1 | 4 | 0 | 0.04 |
| 6628 | David Hughes | 1 | 1 | 4 | 0 | 0.04 |
| 6629 | David Knox | 1 | 1 | 4 | 0 | 0.04 |
| 6630 | David Morgan | 1 | 1 | 4 | 0 | 0.04 |
| 6631 | Dawn Hopkins | 1 | 1 | 4 | 0 | 0.04 |
| 6632 | Debbie Edwards | 1 | 1 | 4 | 0 | 0.04 |
| 6633 | Debra Avery | 1 | 1 | 4 | 0 | 0.04 |
| 6634 | Devin Chan | 1 | 1 | 4 | 0 | 0.04 |
| 6635 | Dierk Reichmann | 1 | 1 | 4 | 0 | 0.04 |
| 6636 | Diya Goyal | 1 | 1 | 4 | 0 | 0.04 |
| 6637 | Donald Nelson | 1 | 1 | 4 | 0 | 0.04 |
| 6638 | Donatello Schiaparelli | 1 | 1 | 4 | 0 | 0.04 |
| 6639 | Douglas Griffin | 1 | 1 | 4 | 0 | 0.04 |
| 6640 | Duane Richardson | 1 | 1 | 4 | 0 | 0.04 |
| 6641 | Dylan Rice | 1 | 1 | 4 | 0 | 0.04 |
| 6642 | Eileen Wiley | 1 | 1 | 4 | 0 | 0.04 |
| 6643 | Elakshi Shukla | 1 | 1 | 4 | 0 | 0.04 |
| 6644 | Elena Olivera Agudo | 1 | 1 | 4 | 0 | 0.04 |
| 6645 | Enno Reinhardt | 1 | 1 | 4 | 0 | 0.04 |
| 6646 | Eric Boyd | 1 | 1 | 4 | 0 | 0.04 |
| 6647 | Eric King | 1 | 1 | 4 | 0 | 0.04 |
| 6648 | Ermanno Rosiello | 1 | 1 | 4 | 0 | 0.04 |
| 6649 | Ernest Mills | 1 | 1 | 4 | 0 | 0.04 |
| 6650 | Evelia Viñas-Maldonado | 1 | 1 | 4 | 0 | 0.04 |
| 6651 | Femke de Koning-Hendriks | 1 | 1 | 4 | 0 | 0.04 |
| 6652 | Ferdinando Nordio | 1 | 1 | 4 | 0 | 0.04 |
| 6653 | Fernanda Lamborghini | 1 | 1 | 4 | 0 | 0.04 |
| 6654 | Gabriel Rosales | 1 | 1 | 4 | 0 | 0.04 |
| 6655 | Gang Guo | 1 | 1 | 4 | 0 | 0.04 |
| 6656 | Gang Lu | 1 | 1 | 4 | 0 | 0.04 |
| 6657 | Gang Xiao | 1 | 1 | 4 | 0 | 0.04 |
| 6658 | Gatik Soni | 1 | 1 | 4 | 0 | 0.04 |
| 6659 | Gemma Gentilini | 1 | 1 | 4 | 0 | 0.04 |
| 6660 | Geraldo Moreno-Bravo | 1 | 1 | 4 | 0 | 0.04 |
| 6661 | Gertraud Franke-Trupp | 1 | 1 | 4 | 0 | 0.04 |
| 6662 | Gianfrancesco Merisi | 1 | 1 | 4 | 0 | 0.04 |
| 6663 | Giorgia Norbiato | 1 | 1 | 4 | 0 | 0.04 |
| 6664 | Greco Duse-Liverotti | 1 | 1 | 4 | 0 | 0.04 |
| 6665 | Guy Voisin | 1 | 1 | 4 | 0 | 0.04 |
| 6666 | Haley Adams | 1 | 1 | 4 | 0 | 0.04 |
| 6667 | Heather Dalton | 1 | 1 | 4 | 0 | 0.04 |
| 6668 | Herr Reinald Roht | 1 | 1 | 4 | 0 | 0.04 |
| 6669 | Herr Wolf-Rüdiger Werner | 1 | 1 | 4 | 0 | 0.04 |
| 6670 | Hiran Sarna | 1 | 1 | 4 | 0 | 0.04 |
| 6671 | Hugo Pareto | 1 | 1 | 4 | 0 | 0.04 |
| 6672 | Ian Dawson | 1 | 1 | 4 | 0 | 0.04 |
| 6673 | Ignatz Jüttner | 1 | 1 | 4 | 0 | 0.04 |
| 6674 | Indranil Bedi | 1 | 1 | 4 | 0 | 0.04 |
| 6675 | Ippazio Lattuada | 1 | 1 | 4 | 0 | 0.04 |
| 6676 | Isabel Wilson | 1 | 1 | 4 | 0 | 0.04 |
| 6677 | Jacob Ramirez | 1 | 1 | 4 | 0 | 0.04 |
| 6678 | Jacob Richards | 1 | 1 | 4 | 0 | 0.04 |
| 6679 | Jacob Rogers | 1 | 1 | 4 | 0 | 0.04 |
| 6680 | Jacqueline Bowen | 1 | 1 | 4 | 0 | 0.04 |
| 6681 | Jake Bailey | 1 | 1 | 4 | 0 | 0.04 |
| 6682 | James Hart | 1 | 1 | 4 | 0 | 0.04 |
| 6683 | Janice Fuentes | 1 | 1 | 4 | 0 | 0.04 |
| 6684 | Jared Snow | 1 | 1 | 4 | 0 | 0.04 |
| 6685 | Jason Miller | 1 | 1 | 4 | 0 | 0.04 |
| 6686 | Jeffrey Butler | 1 | 1 | 4 | 0 | 0.04 |
| 6687 | Jenna York | 1 | 1 | 4 | 0 | 0.04 |
| 6688 | Jennifer Adams | 1 | 1 | 4 | 0 | 0.04 |
| 6689 | Jennifer Boyer | 1 | 1 | 4 | 0 | 0.04 |
| 6690 | Jennifer Harris | 1 | 1 | 4 | 0 | 0.04 |
| 6691 | Jennifer Spencer | 1 | 1 | 4 | 0 | 0.04 |
| 6692 | Jennifer Vang | 1 | 1 | 4 | 0 | 0.04 |
| 6693 | Jessica Moreno | 1 | 1 | 4 | 0 | 0.04 |
| 6694 | Jessica Schroeder | 1 | 1 | 4 | 0 | 0.04 |
| 6695 | Jessica Valentine | 1 | 1 | 4 | 0 | 0.04 |
| 6696 | Jie Qian | 1 | 1 | 4 | 0 | 0.04 |
| 6697 | Jill Gardner | 1 | 1 | 4 | 0 | 0.04 |
| 6698 | Jing Zheng | 1 | 1 | 4 | 0 | 0.04 |
| 6699 | Jo Stewart | 1 | 1 | 4 | 0 | 0.04 |
| 6700 | Joanne Fowler | 1 | 1 | 4 | 0 | 0.04 |
| 6701 | Jodi Gilbert | 1 | 1 | 4 | 0 | 0.04 |
| 6702 | Jonathan Lawson | 1 | 1 | 4 | 0 | 0.04 |
| 6703 | Jordan Lawrence | 1 | 1 | 4 | 0 | 0.04 |
| 6704 | Joseph Allen | 1 | 1 | 4 | 0 | 0.04 |
| 6705 | Joshua Watson | 1 | 1 | 4 | 0 | 0.04 |
| 6706 | Juan Han | 1 | 1 | 4 | 0 | 0.04 |
| 6707 | Judy Elliott | 1 | 1 | 4 | 0 | 0.04 |
| 6708 | Julia Allen | 1 | 1 | 4 | 0 | 0.04 |
| 6709 | Juri Textor | 1 | 1 | 4 | 0 | 0.04 |
| 6710 | Justin Ellison | 1 | 1 | 4 | 0 | 0.04 |
| 6711 | Kacper Panasewicz | 1 | 1 | 4 | 0 | 0.04 |
| 6712 | Kaira Dutt | 1 | 1 | 4 | 0 | 0.04 |
| 6713 | Karen Jackson | 1 | 1 | 4 | 0 | 0.04 |
| 6714 | Karen Thomas | 1 | 1 | 4 | 0 | 0.04 |
| 6715 | Karen Valdez | 1 | 1 | 4 | 0 | 0.04 |
| 6716 | Kathleen Duran | 1 | 1 | 4 | 0 | 0.04 |
| 6717 | Kathryn Spencer | 1 | 1 | 4 | 0 | 0.04 |
| 6718 | Kayla Barnes | 1 | 1 | 4 | 0 | 0.04 |
| 6719 | Kelly Long | 1 | 1 | 4 | 0 | 0.04 |
| 6720 | Kelly Lopez | 1 | 1 | 4 | 0 | 0.04 |
| 6721 | Kenneth Banks | 1 | 1 | 4 | 0 | 0.04 |
| 6722 | Kenneth Douglas | 1 | 1 | 4 | 0 | 0.04 |
| 6723 | Kevin Cooke | 1 | 1 | 4 | 0 | 0.04 |
| 6724 | Kevin Pearson | 1 | 1 | 4 | 0 | 0.04 |
| 6725 | Kevin Ross | 1 | 1 | 4 | 0 | 0.04 |
| 6726 | Kimberly Hernandez | 1 | 1 | 4 | 0 | 0.04 |
| 6727 | Kimberly Lopez | 1 | 1 | 4 | 0 | 0.04 |
| 6728 | Klaus-Günter Bender | 1 | 1 | 4 | 0 | 0.04 |
| 6729 | Konstantinos Wende | 1 | 1 | 4 | 0 | 0.04 |
| 6730 | Kristina Cowan | 1 | 1 | 4 | 0 | 0.04 |
| 6731 | Kristina Martinez | 1 | 1 | 4 | 0 | 0.04 |
| 6732 | Krystal Moody | 1 | 1 | 4 | 0 | 0.04 |
| 6733 | Kumiko Saito | 1 | 1 | 4 | 0 | 0.04 |
| 6734 | Kyle Mason | 1 | 1 | 4 | 0 | 0.04 |
| 6735 | Laura Badoglio | 1 | 1 | 4 | 0 | 0.04 |
| 6736 | Laura Davis | 1 | 1 | 4 | 0 | 0.04 |
| 6737 | Laurie Rodriguez | 1 | 1 | 4 | 0 | 0.04 |
| 6738 | Lei Chen | 1 | 1 | 4 | 0 | 0.04 |
| 6739 | Leon Hrabia | 1 | 1 | 4 | 0 | 0.04 |
| 6740 | Leoncio de Moliner | 1 | 1 | 4 | 0 | 0.04 |
| 6741 | Lia Grant | 1 | 1 | 4 | 0 | 0.04 |
| 6742 | Liliana Morellato | 1 | 1 | 4 | 0 | 0.04 |
| 6743 | Lina Tirabassi | 1 | 1 | 4 | 0 | 0.04 |
| 6744 | Lindsay Lyons | 1 | 1 | 4 | 0 | 0.04 |
| 6745 | Lindsey Diaz | 1 | 1 | 4 | 0 | 0.04 |
| 6746 | Lori Bowers | 1 | 1 | 4 | 0 | 0.04 |
| 6747 | Ludovica Tamborini-Paolucci | 1 | 1 | 4 | 0 | 0.04 |
| 6748 | Madhup Ganesh | 1 | 1 | 4 | 0 | 0.04 |
| 6749 | Magnus Speer | 1 | 1 | 4 | 0 | 0.04 |
| 6750 | Marcia Florencia Carmona Cuéllar | 1 | 1 | 4 | 0 | 0.04 |
| 6751 | Margaret Vargas | 1 | 1 | 4 | 0 | 0.04 |
| 6752 | Marie Munoz | 1 | 1 | 4 | 0 | 0.04 |
| 6753 | Marilyn Douglas | 1 | 1 | 4 | 0 | 0.04 |
| 6754 | Mary Boyd | 1 | 1 | 4 | 0 | 0.04 |
| 6755 | Mary King | 1 | 1 | 4 | 0 | 0.04 |
| 6756 | Mary Parsons | 1 | 1 | 4 | 0 | 0.04 |
| 6757 | Matthew Conner PhD | 1 | 1 | 4 | 0 | 0.04 |
| 6758 | Matthew Dominguez | 1 | 1 | 4 | 0 | 0.04 |
| 6759 | Matthew Howell | 1 | 1 | 4 | 0 | 0.04 |
| 6760 | Maurice Harrison | 1 | 1 | 4 | 0 | 0.04 |
| 6761 | Mees Oude Heer | 1 | 1 | 4 | 0 | 0.04 |
| 6762 | Melania Filangieri | 1 | 1 | 4 | 0 | 0.04 |
| 6763 | Mercedes Salata | 1 | 1 | 4 | 0 | 0.04 |
| 6764 | Michael Baker | 1 | 1 | 4 | 0 | 0.04 |
| 6765 | Michael Bennett | 1 | 1 | 4 | 0 | 0.04 |
| 6766 | Michael Benson | 1 | 1 | 4 | 0 | 0.04 |
| 6767 | Michael Flowers | 1 | 1 | 4 | 0 | 0.04 |
| 6768 | Michael Glenn | 1 | 1 | 4 | 0 | 0.04 |
| 6769 | Michael Gregory | 1 | 1 | 4 | 0 | 0.04 |
| 6770 | Michael Jefferson | 1 | 1 | 4 | 0 | 0.04 |
| 6771 | Michael Mann | 1 | 1 | 4 | 0 | 0.04 |
| 6772 | Michael Montgomery | 1 | 1 | 4 | 0 | 0.04 |
| 6773 | Michael Perez | 1 | 1 | 4 | 0 | 0.04 |
| 6774 | Michal Žák | 1 | 1 | 4 | 0 | 0.04 |
| 6775 | Michelle Atkins | 1 | 1 | 4 | 0 | 0.04 |
| 6776 | Michelle Monnier | 1 | 1 | 4 | 0 | 0.04 |
| 6777 | Michelle Weiss | 1 | 1 | 4 | 0 | 0.04 |
| 6778 | Miki Sato | 1 | 1 | 4 | 0 | 0.04 |
| 6779 | Miluše Dušková | 1 | 1 | 4 | 0 | 0.04 |
| 6780 | Min Feng | 1 | 1 | 4 | 0 | 0.04 |
| 6781 | Min Lai | 1 | 1 | 4 | 0 | 0.04 |
| 6782 | Min Luo | 1 | 1 | 4 | 0 | 0.04 |
| 6783 | Ming Guo | 1 | 1 | 4 | 0 | 0.04 |
| 6784 | Miss Jeanette Marshall | 1 | 1 | 4 | 0 | 0.04 |
| 6785 | Misty Reyes | 1 | 1 | 4 | 0 | 0.04 |
| 6786 | Mitchell Bryan | 1 | 1 | 4 | 0 | 0.04 |
| 6787 | Momoko Ito | 1 | 1 | 4 | 0 | 0.04 |
| 6788 | Monika Bochnia | 1 | 1 | 4 | 0 | 0.04 |
| 6789 | Myra Devan | 1 | 1 | 4 | 0 | 0.04 |
| 6790 | Na Wang | 1 | 1 | 4 | 0 | 0.04 |
| 6791 | Naděžda Pešková | 1 | 1 | 4 | 0 | 0.04 |
| 6792 | Nancy Wright | 1 | 1 | 4 | 0 | 0.04 |
| 6793 | Naoko Yamada | 1 | 1 | 4 | 0 | 0.04 |
| 6794 | Navya Barad | 1 | 1 | 4 | 0 | 0.04 |
| 6795 | Nicholas Pineda | 1 | 1 | 4 | 0 | 0.04 |
| 6796 | Nichole Benton | 1 | 1 | 4 | 0 | 0.04 |
| 6797 | Nicoletta Soffici | 1 | 1 | 4 | 0 | 0.04 |
| 6798 | Nina Flaiano | 1 | 1 | 4 | 0 | 0.04 |
| 6799 | Océane Bouchet | 1 | 1 | 4 | 0 | 0.04 |
| 6800 | Paloma Merisi | 1 | 1 | 4 | 0 | 0.04 |
| 6801 | Pamela Crane | 1 | 1 | 4 | 0 | 0.04 |
| 6802 | Pamela Kent | 1 | 1 | 4 | 0 | 0.04 |
| 6803 | Pamela Mitchell | 1 | 1 | 4 | 0 | 0.04 |
| 6804 | Paul Johnson | 1 | 1 | 4 | 0 | 0.04 |
| 6805 | Paul-Louis Benard | 1 | 1 | 4 | 0 | 0.04 |
| 6806 | Perry Thompson | 1 | 1 | 4 | 0 | 0.04 |
| 6807 | Phillip Kane | 1 | 1 | 4 | 0 | 0.04 |
| 6808 | Piermaria Modugno | 1 | 1 | 4 | 0 | 0.04 |
| 6809 | Ping Feng | 1 | 1 | 4 | 0 | 0.04 |
| 6810 | Ping Kang | 1 | 1 | 4 | 0 | 0.04 |
| 6811 | Piya Mann | 1 | 1 | 4 | 0 | 0.04 |
| 6812 | Qiang Cai | 1 | 1 | 4 | 0 | 0.04 |
| 6813 | Qiang Gong | 1 | 1 | 4 | 0 | 0.04 |
| 6814 | Rachel Thompson | 1 | 1 | 4 | 0 | 0.04 |
| 6815 | Raghav Garde | 1 | 1 | 4 | 0 | 0.04 |
| 6816 | Ramona Camiscione | 1 | 1 | 4 | 0 | 0.04 |
| 6817 | Ranbir Balay | 1 | 1 | 4 | 0 | 0.04 |
| 6818 | Randy Vasquez | 1 | 1 | 4 | 0 | 0.04 |
| 6819 | Regina Hensley | 1 | 1 | 4 | 0 | 0.04 |
| 6820 | Rhonda Miller | 1 | 1 | 4 | 0 | 0.04 |
| 6821 | Ricardo Ward | 1 | 1 | 4 | 0 | 0.04 |
| 6822 | Robert Harris | 1 | 1 | 4 | 0 | 0.04 |
| 6823 | Robert Mathis | 1 | 1 | 4 | 0 | 0.04 |
| 6824 | Robert Quinn | 1 | 1 | 4 | 0 | 0.04 |
| 6825 | Robin Harris | 1 | 1 | 4 | 0 | 0.04 |
| 6826 | Roksana Wlaźlak | 1 | 1 | 4 | 0 | 0.04 |
| 6827 | Romil Sibal | 1 | 1 | 4 | 0 | 0.04 |
| 6828 | Ronald Parks | 1 | 1 | 4 | 0 | 0.04 |
| 6829 | Ronald Yates | 1 | 1 | 4 | 0 | 0.04 |
| 6830 | Roy Miller | 1 | 1 | 4 | 0 | 0.04 |
| 6831 | Ryan Pollard | 1 | 1 | 4 | 0 | 0.04 |
| 6832 | Sabina Hrušková | 1 | 1 | 4 | 0 | 0.04 |
| 6833 | Sabine Ollivier-Morel | 1 | 1 | 4 | 0 | 0.04 |
| 6834 | Samantha Munoz | 1 | 1 | 4 | 0 | 0.04 |
| 6835 | Samantha Padilla | 1 | 1 | 4 | 0 | 0.04 |
| 6836 | Samar Luthra | 1 | 1 | 4 | 0 | 0.04 |
| 6837 | Samiha Chander | 1 | 1 | 4 | 0 | 0.04 |
| 6838 | Sana Batta | 1 | 1 | 4 | 0 | 0.04 |
| 6839 | Sana Sunder | 1 | 1 | 4 | 0 | 0.04 |
| 6840 | Sara Berger | 1 | 1 | 4 | 0 | 0.04 |
| 6841 | Sarah Clark | 1 | 1 | 4 | 0 | 0.04 |
| 6842 | Sarah Gray | 1 | 1 | 4 | 0 | 0.04 |
| 6843 | Sarah Hunter | 1 | 1 | 4 | 0 | 0.04 |
| 6844 | Sawyer and the Frontiers | 1 | 1 | 4 | 0 | 0.04 |
| 6845 | Scott Burke | 1 | 1 | 4 | 0 | 0.04 |
| 6846 | Scott Garcia | 1 | 1 | 4 | 0 | 0.04 |
| 6847 | Sean Jackson | 1 | 1 | 4 | 0 | 0.04 |
| 6848 | Sean Lewis | 1 | 1 | 4 | 0 | 0.04 |
| 6849 | Sean Mendoza | 1 | 1 | 4 | 0 | 0.04 |
| 6850 | Sean Phillips | 1 | 1 | 4 | 0 | 0.04 |
| 6851 | Sean Rogers | 1 | 1 | 4 | 0 | 0.04 |
| 6852 | Seve Francisco | 1 | 1 | 4 | 0 | 0.04 |
| 6853 | Sonia Innocenti-Gasperi | 1 | 1 | 4 | 0 | 0.04 |
| 6854 | Stephanie Johnson | 1 | 1 | 4 | 0 | 0.04 |
| 6855 | Stephen Vazquez | 1 | 1 | 4 | 0 | 0.04 |
| 6856 | Steven Calderon | 1 | 1 | 4 | 0 | 0.04 |
| 6857 | Steven Hobbs | 1 | 1 | 4 | 0 | 0.04 |
| 6858 | Stéphanie Parent | 1 | 1 | 4 | 0 | 0.04 |
| 6859 | Susan Brown | 1 | 1 | 4 | 0 | 0.04 |
| 6860 | Susan Spencer | 1 | 1 | 4 | 0 | 0.04 |
| 6861 | Susan Wong | 1 | 1 | 4 | 0 | 0.04 |
| 6862 | Sylwia Skowyra | 1 | 1 | 4 | 0 | 0.04 |
| 6863 | Taimur Iyer | 1 | 1 | 4 | 0 | 0.04 |
| 6864 | Tamara Douglas | 1 | 1 | 4 | 0 | 0.04 |
| 6865 | Tammy Camacho | 1 | 1 | 4 | 0 | 0.04 |
| 6866 | Tao Shi | 1 | 1 | 4 | 0 | 0.04 |
| 6867 | Tara Timmermans | 1 | 1 | 4 | 0 | 0.04 |
| 6868 | Terri Johnson | 1 | 1 | 4 | 0 | 0.04 |
| 6869 | Terry Nelson | 1 | 1 | 4 | 0 | 0.04 |
| 6870 | Thekla Schuster | 1 | 1 | 4 | 0 | 0.04 |
| 6871 | Theresa Jones | 1 | 1 | 4 | 0 | 0.04 |
| 6872 | Thilo Schmiedt | 1 | 1 | 4 | 0 | 0.04 |
| 6873 | Thomas Carter | 1 | 1 | 4 | 0 | 0.04 |
| 6874 | Thomas Palmer | 1 | 1 | 4 | 0 | 0.04 |
| 6875 | Tiffany Martinez | 1 | 1 | 4 | 0 | 0.04 |
| 6876 | Tim Slingerland | 1 | 1 | 4 | 0 | 0.04 |
| 6877 | Timothy Hall | 1 | 1 | 4 | 0 | 0.04 |
| 6878 | Timothy Padilla | 1 | 1 | 4 | 0 | 0.04 |
| 6879 | Timothy Robinson | 1 | 1 | 4 | 0 | 0.04 |
| 6880 | Todd Molina | 1 | 1 | 4 | 0 | 0.04 |
| 6881 | Tommy Murphy | 1 | 1 | 4 | 0 | 0.04 |
| 6882 | Urban Budig | 1 | 1 | 4 | 0 | 0.04 |
| 6883 | Urte Bachmann | 1 | 1 | 4 | 0 | 0.04 |
| 6884 | Venancio Belletini | 1 | 1 | 4 | 0 | 0.04 |
| 6885 | Veronica Koch | 1 | 1 | 4 | 0 | 0.04 |
| 6886 | Vicki Shepard | 1 | 1 | 4 | 0 | 0.04 |
| 6887 | Victor Miller | 1 | 1 | 4 | 0 | 0.04 |
| 6888 | Victoria Vazquez | 1 | 1 | 4 | 0 | 0.04 |
| 6889 | Viviana Escrivá Porcel | 1 | 1 | 4 | 0 | 0.04 |
| 6890 | Véronique Bernard | 1 | 1 | 4 | 0 | 0.04 |
| 6891 | Wanda Ray | 1 | 1 | 4 | 0 | 0.04 |
| 6892 | Wesley Ford | 1 | 1 | 4 | 0 | 0.04 |
| 6893 | William Ball | 1 | 1 | 4 | 0 | 0.04 |
| 6894 | William Diaz | 1 | 1 | 4 | 0 | 0.04 |
| 6895 | Willie Phelps | 1 | 1 | 4 | 0 | 0.04 |
| 6896 | Xiulan Mao | 1 | 1 | 4 | 0 | 0.04 |
| 6897 | Xiuying Su | 1 | 1 | 4 | 0 | 0.04 |
| 6898 | Yan Xiang | 1 | 1 | 4 | 0 | 0.04 |
| 6899 | Yan Xu | 1 | 1 | 4 | 0 | 0.04 |
| 6900 | Yasuhiro Yoshida | 1 | 1 | 4 | 0 | 0.04 |
| 6901 | Yong Xu | 1 | 1 | 4 | 0 | 0.04 |
| 6902 | Yves Gaudin | 1 | 1 | 4 | 0 | 0.04 |
| 6903 | Yvonne Morris | 1 | 1 | 4 | 0 | 0.04 |
| 6904 | Zachary Cole | 1 | 1 | 4 | 0 | 0.04 |
| 6905 | Émile Didier | 1 | 1 | 4 | 0 | 0.04 |
| 6906 | Éric Lamy | 1 | 1 | 4 | 0 | 0.04 |
| 6907 | Éric Louis-Lévy | 1 | 1 | 4 | 0 | 0.04 |
| 6908 | Aayush Cheema | 1 | 1 | 3 | 0 | 0.03 |
| 6909 | Adam Allen | 1 | 1 | 3 | 0 | 0.03 |
| 6910 | Adam Carter | 1 | 1 | 3 | 0 | 0.03 |
| 6911 | Adam Gill | 1 | 1 | 3 | 0 | 0.03 |
| 6912 | Adrian Jeszka | 1 | 1 | 3 | 0 | 0.03 |
| 6913 | Aitor Alcántara Diez | 1 | 1 | 3 | 0 | 0.03 |
| 6914 | Alain Delannoy | 1 | 1 | 3 | 0 | 0.03 |
| 6915 | Alan Bray | 1 | 1 | 3 | 0 | 0.03 |
| 6916 | Aleksander Grześków | 1 | 1 | 3 | 0 | 0.03 |
| 6917 | Aleksander Sypień | 1 | 1 | 3 | 0 | 0.03 |
| 6918 | Alex Bridges | 1 | 1 | 3 | 0 | 0.03 |
| 6919 | Alex Leblanc | 1 | 1 | 3 | 0 | 0.03 |
| 6920 | Alexander Lawrence | 1 | 1 | 3 | 0 | 0.03 |
| 6921 | Alexandra King | 1 | 1 | 3 | 0 | 0.03 |
| 6922 | Alexandra Mcdaniel | 1 | 1 | 3 | 0 | 0.03 |
| 6923 | Alexandra Scott | 1 | 1 | 3 | 0 | 0.03 |
| 6924 | Alexei Gotthard | 1 | 1 | 3 | 0 | 0.03 |
| 6925 | Alexis Moore | 1 | 1 | 3 | 0 | 0.03 |
| 6926 | Alisha Hartman | 1 | 1 | 3 | 0 | 0.03 |
| 6927 | Alix Chevallier | 1 | 1 | 3 | 0 | 0.03 |
| 6928 | Alma Vollbrecht | 1 | 1 | 3 | 0 | 0.03 |
| 6929 | Amanda Davis | 1 | 1 | 3 | 0 | 0.03 |
| 6930 | Amber Nguyen | 1 | 1 | 3 | 0 | 0.03 |
| 6931 | Amber Park | 1 | 1 | 3 | 0 | 0.03 |
| 6932 | Amber Ramsey | 1 | 1 | 3 | 0 | 0.03 |
| 6933 | Amber Rodriguez | 1 | 1 | 3 | 0 | 0.03 |
| 6934 | Amedeo Mimun | 1 | 1 | 3 | 0 | 0.03 |
| 6935 | Amy Alexander | 1 | 1 | 3 | 0 | 0.03 |
| 6936 | Amy Barnes | 1 | 1 | 3 | 0 | 0.03 |
| 6937 | Amy Bright | 1 | 1 | 3 | 0 | 0.03 |
| 6938 | Amy Campbell | 1 | 1 | 3 | 0 | 0.03 |
| 6939 | Amy Riley | 1 | 1 | 3 | 0 | 0.03 |
| 6940 | Amélie Peltier | 1 | 1 | 3 | 0 | 0.03 |
| 6941 | Andrew Garcia | 1 | 1 | 3 | 0 | 0.03 |
| 6942 | Andrew Nolan | 1 | 1 | 3 | 0 | 0.03 |
| 6943 | Angela Collins | 1 | 1 | 3 | 0 | 0.03 |
| 6944 | Angela Lopez | 1 | 1 | 3 | 0 | 0.03 |
| 6945 | Angela Perez | 1 | 1 | 3 | 0 | 0.03 |
| 6946 | Animated Antics | 1 | 1 | 3 | 0 | 0.03 |
| 6947 | Anna Fechner | 1 | 1 | 3 | 0 | 0.03 |
| 6948 | Anne Frederick | 1 | 1 | 3 | 0 | 0.03 |
| 6949 | Anne Verwoert-Slagmolen | 1 | 1 | 3 | 0 | 0.03 |
| 6950 | Annetta Molesini | 1 | 1 | 3 | 0 | 0.03 |
| 6951 | Anouk Carre | 1 | 1 | 3 | 0 | 0.03 |
| 6952 | Anthony Peters | 1 | 1 | 3 | 0 | 0.03 |
| 6953 | Antonia Steinberg-Löffler | 1 | 1 | 3 | 0 | 0.03 |
| 6954 | Antonio Morse | 1 | 1 | 3 | 0 | 0.03 |
| 6955 | Antonio Schroeder | 1 | 1 | 3 | 0 | 0.03 |
| 6956 | April Mills | 1 | 1 | 3 | 0 | 0.03 |
| 6957 | April Nelson | 1 | 1 | 3 | 0 | 0.03 |
| 6958 | Ashley Huang | 1 | 1 | 3 | 0 | 0.03 |
| 6959 | Ashley Mahoney | 1 | 1 | 3 | 0 | 0.03 |
| 6960 | Ashley Olsen | 1 | 1 | 3 | 0 | 0.03 |
| 6961 | Audrey Frye | 1 | 1 | 3 | 0 | 0.03 |
| 6962 | Auguste de la Laroche | 1 | 1 | 3 | 0 | 0.03 |
| 6963 | Augusto Franzese | 1 | 1 | 3 | 0 | 0.03 |
| 6964 | Aurora Vendetti | 1 | 1 | 3 | 0 | 0.03 |
| 6965 | Aysel Scheibe | 1 | 1 | 3 | 0 | 0.03 |
| 6966 | Beatrice Albers | 1 | 1 | 3 | 0 | 0.03 |
| 6967 | Benjamin Dupuis-Lévy | 1 | 1 | 3 | 0 | 0.03 |
| 6968 | Bernard-Alain Parent | 1 | 1 | 3 | 0 | 0.03 |
| 6969 | Bernardo Josep Mayol Manjón | 1 | 1 | 3 | 0 | 0.03 |
| 6970 | Bonnie Roberts | 1 | 1 | 3 | 0 | 0.03 |
| 6971 | Bradley Anderson | 1 | 1 | 3 | 0 | 0.03 |
| 6972 | Bradley Gray | 1 | 1 | 3 | 0 | 0.03 |
| 6973 | Brandi Sutton | 1 | 1 | 3 | 0 | 0.03 |
| 6974 | Brandon Banks | 1 | 1 | 3 | 0 | 0.03 |
| 6975 | Brenda Boyd | 1 | 1 | 3 | 0 | 0.03 |
| 6976 | Brett Terry | 1 | 1 | 3 | 0 | 0.03 |
| 6977 | Brian Olsen | 1 | 1 | 3 | 0 | 0.03 |
| 6978 | Brian Oneal | 1 | 1 | 3 | 0 | 0.03 |
| 6979 | Brian Vincent | 1 | 1 | 3 | 0 | 0.03 |
| 6980 | Briana Harris | 1 | 1 | 3 | 0 | 0.03 |
| 6981 | Brianna Hopkins | 1 | 1 | 3 | 0 | 0.03 |
| 6982 | Brigitte Langlois | 1 | 1 | 3 | 0 | 0.03 |
| 6983 | Carl Benjamin | 1 | 1 | 3 | 0 | 0.03 |
| 6984 | Carla Holden | 1 | 1 | 3 | 0 | 0.03 |
| 6985 | Carolyn Morgan | 1 | 1 | 3 | 0 | 0.03 |
| 6986 | Catherine Perez | 1 | 1 | 3 | 0 | 0.03 |
| 6987 | Catherine Roberts | 1 | 1 | 3 | 0 | 0.03 |
| 6988 | Cato Meyer | 1 | 1 | 3 | 0 | 0.03 |
| 6989 | Cesar Nixon | 1 | 1 | 3 | 0 | 0.03 |
| 6990 | Chao Yin | 1 | 1 | 3 | 0 | 0.03 |
| 6991 | Chelsea Blake | 1 | 1 | 3 | 0 | 0.03 |
| 6992 | Chirag Bahri | 1 | 1 | 3 | 0 | 0.03 |
| 6993 | Chris Cook | 1 | 1 | 3 | 0 | 0.03 |
| 6994 | Christian Gray | 1 | 1 | 3 | 0 | 0.03 |
| 6995 | Christina Mckay | 1 | 1 | 3 | 0 | 0.03 |
| 6996 | Christine Brown | 1 | 1 | 3 | 0 | 0.03 |
| 6997 | Christine Johnson | 1 | 1 | 3 | 0 | 0.03 |
| 6998 | Christopher Reilly | 1 | 1 | 3 | 0 | 0.03 |
| 6999 | Christopher Wood | 1 | 1 | 3 | 0 | 0.03 |
| 7000 | Christopher Young | 1 | 1 | 3 | 0 | 0.03 |
| 7001 | Chuy Calderon Chaves | 1 | 1 | 3 | 0 | 0.03 |
| 7002 | Cindy Hernandez | 1 | 1 | 3 | 0 | 0.03 |
| 7003 | Cindy Parker | 1 | 1 | 3 | 0 | 0.03 |
| 7004 | Colton Williams | 1 | 1 | 3 | 0 | 0.03 |
| 7005 | Cory Garrett | 1 | 1 | 3 | 0 | 0.03 |
| 7006 | Courtney Johnston | 1 | 1 | 3 | 0 | 0.03 |
| 7007 | Cynthia Jones | 1 | 1 | 3 | 0 | 0.03 |
| 7008 | Damiano Gelli-Verga | 1 | 1 | 3 | 0 | 0.03 |
| 7009 | Dana Baker | 1 | 1 | 3 | 0 | 0.03 |
| 7010 | Dana Medina | 1 | 1 | 3 | 0 | 0.03 |
| 7011 | Dana Perkins | 1 | 1 | 3 | 0 | 0.03 |
| 7012 | Daniel Oneill | 1 | 1 | 3 | 0 | 0.03 |
| 7013 | Daniel Williams | 1 | 1 | 3 | 0 | 0.03 |
| 7014 | Danny Lindsey | 1 | 1 | 3 | 0 | 0.03 |
| 7015 | Darshit Mannan | 1 | 1 | 3 | 0 | 0.03 |
| 7016 | David Choi | 1 | 1 | 3 | 0 | 0.03 |
| 7017 | David Cruz | 1 | 1 | 3 | 0 | 0.03 |
| 7018 | David Maddox | 1 | 1 | 3 | 0 | 0.03 |
| 7019 | David Orr | 1 | 1 | 3 | 0 | 0.03 |
| 7020 | David Richardson | 1 | 1 | 3 | 0 | 0.03 |
| 7021 | Dawn Massey | 1 | 1 | 3 | 0 | 0.03 |
| 7022 | Dawn Mcguire | 1 | 1 | 3 | 0 | 0.03 |
| 7023 | Deborah Aguilar | 1 | 1 | 3 | 0 | 0.03 |
| 7024 | Deborah Martinez | 1 | 1 | 3 | 0 | 0.03 |
| 7025 | Deborah Norton | 1 | 1 | 3 | 0 | 0.03 |
| 7026 | Deborah Osborne | 1 | 1 | 3 | 0 | 0.03 |
| 7027 | Debra Sims | 1 | 1 | 3 | 0 | 0.03 |
| 7028 | Denise Perez | 1 | 1 | 3 | 0 | 0.03 |
| 7029 | Derek Robinson | 1 | 1 | 3 | 0 | 0.03 |
| 7030 | Destiny Griffin | 1 | 1 | 3 | 0 | 0.03 |
| 7031 | Devon White | 1 | 1 | 3 | 0 | 0.03 |
| 7032 | Dhanush Baria | 1 | 1 | 3 | 0 | 0.03 |
| 7033 | Diane Anderson | 1 | 1 | 3 | 0 | 0.03 |
| 7034 | Divij Dora | 1 | 1 | 3 | 0 | 0.03 |
| 7035 | Dominique Delacruz | 1 | 1 | 3 | 0 | 0.03 |
| 7036 | Donna Nelson | 1 | 1 | 3 | 0 | 0.03 |
| 7037 | Doris Hatfield | 1 | 1 | 3 | 0 | 0.03 |
| 7038 | Eckard Werner | 1 | 1 | 3 | 0 | 0.03 |
| 7039 | Edward Little | 1 | 1 | 3 | 0 | 0.03 |
| 7040 | Edward Randolph | 1 | 1 | 3 | 0 | 0.03 |
| 7041 | Elizabeth Walters | 1 | 1 | 3 | 0 | 0.03 |
| 7042 | Emily Huynh | 1 | 1 | 3 | 0 | 0.03 |
| 7043 | Eric Armstrong | 1 | 1 | 3 | 0 | 0.03 |
| 7044 | Erica Chandler | 1 | 1 | 3 | 0 | 0.03 |
| 7045 | Erica Herrera | 1 | 1 | 3 | 0 | 0.03 |
| 7046 | Erik Huang Jr. | 1 | 1 | 3 | 0 | 0.03 |
| 7047 | Erin Mitchell | 1 | 1 | 3 | 0 | 0.03 |
| 7048 | Ernest Clark | 1 | 1 | 3 | 0 | 0.03 |
| 7049 | Ethan Moore | 1 | 1 | 3 | 0 | 0.03 |
| 7050 | Fang Jin | 1 | 1 | 3 | 0 | 0.03 |
| 7051 | Fang Wang | 1 | 1 | 3 | 0 | 0.03 |
| 7052 | Fanny Dörschner | 1 | 1 | 3 | 0 | 0.03 |
| 7053 | Ferenc Mälzer | 1 | 1 | 3 | 0 | 0.03 |
| 7054 | Fidel Gras Aller | 1 | 1 | 3 | 0 | 0.03 |
| 7055 | Flavio del Galán | 1 | 1 | 3 | 0 | 0.03 |
| 7056 | Flora Casaleggio-Endrizzi | 1 | 1 | 3 | 0 | 0.03 |
| 7057 | Frederick Jackson Jr. | 1 | 1 | 3 | 0 | 0.03 |
| 7058 | Fredo Piccinni | 1 | 1 | 3 | 0 | 0.03 |
| 7059 | Frieda Mitschke | 1 | 1 | 3 | 0 | 0.03 |
| 7060 | Gang Feng | 1 | 1 | 3 | 0 | 0.03 |
| 7061 | George Gutierrez | 1 | 1 | 3 | 0 | 0.03 |
| 7062 | Gerald Collins | 1 | 1 | 3 | 0 | 0.03 |
| 7063 | Giesela Kuhl | 1 | 1 | 3 | 0 | 0.03 |
| 7064 | Gina Miller | 1 | 1 | 3 | 0 | 0.03 |
| 7065 | Gionata Toldo | 1 | 1 | 3 | 0 | 0.03 |
| 7066 | Greca Canali | 1 | 1 | 3 | 0 | 0.03 |
| 7067 | Gregory Hansen | 1 | 1 | 3 | 0 | 0.03 |
| 7068 | Guillaume Cohen du Leduc | 1 | 1 | 3 | 0 | 0.03 |
| 7069 | Guillaume Petitjean | 1 | 1 | 3 | 0 | 0.03 |
| 7070 | Guiying Wei | 1 | 1 | 3 | 0 | 0.03 |
| 7071 | Guiying Zhu | 1 | 1 | 3 | 0 | 0.03 |
| 7072 | Hannah Hopkins | 1 | 1 | 3 | 0 | 0.03 |
| 7073 | Heather Kennedy | 1 | 1 | 3 | 0 | 0.03 |
| 7074 | Heather Velasquez | 1 | 1 | 3 | 0 | 0.03 |
| 7075 | Heather Wallace | 1 | 1 | 3 | 0 | 0.03 |
| 7076 | Henrik Seifert | 1 | 1 | 3 | 0 | 0.03 |
| 7077 | Ida Vigliotti | 1 | 1 | 3 | 0 | 0.03 |
| 7078 | Ignatz Thanel-Hornich | 1 | 1 | 3 | 0 | 0.03 |
| 7079 | Ildiko Wesack | 1 | 1 | 3 | 0 | 0.03 |
| 7080 | Isa Carmichael | 1 | 1 | 3 | 0 | 0.03 |
| 7081 | Isabella Turner | 1 | 1 | 3 | 0 | 0.03 |
| 7082 | Isabelle Godfrey van Alemannië | 1 | 1 | 3 | 0 | 0.03 |
| 7083 | Ise Scardino | 1 | 1 | 3 | 0 | 0.03 |
| 7084 | Ivo Ziegert | 1 | 1 | 3 | 0 | 0.03 |
| 7085 | Jackie Johnston | 1 | 1 | 3 | 0 | 0.03 |
| 7086 | Jacob Arnold | 1 | 1 | 3 | 0 | 0.03 |
| 7087 | Jacob Gomez | 1 | 1 | 3 | 0 | 0.03 |
| 7088 | Jacob Romero | 1 | 1 | 3 | 0 | 0.03 |
| 7089 | Jacqueline Miller | 1 | 1 | 3 | 0 | 0.03 |
| 7090 | Jacques Imbert de la Munoz | 1 | 1 | 3 | 0 | 0.03 |
| 7091 | James Calderon | 1 | 1 | 3 | 0 | 0.03 |
| 7092 | James Middleton | 1 | 1 | 3 | 0 | 0.03 |
| 7093 | James Simon | 1 | 1 | 3 | 0 | 0.03 |
| 7094 | Jamie Smith | 1 | 1 | 3 | 0 | 0.03 |
| 7095 | Jason Chavez | 1 | 1 | 3 | 0 | 0.03 |
| 7096 | Jason Jones | 1 | 1 | 3 | 0 | 0.03 |
| 7097 | Jason Mckenzie | 1 | 1 | 3 | 0 | 0.03 |
| 7098 | Jeanette Bass | 1 | 1 | 3 | 0 | 0.03 |
| 7099 | Jeff Farmer | 1 | 1 | 3 | 0 | 0.03 |
| 7100 | Jeffrey Knight | 1 | 1 | 3 | 0 | 0.03 |
| 7101 | Jennifer Allen | 1 | 1 | 3 | 0 | 0.03 |
| 7102 | Jennifer Garcia | 1 | 1 | 3 | 0 | 0.03 |
| 7103 | Jeremy Griffith | 1 | 1 | 3 | 0 | 0.03 |
| 7104 | Jeremy Jones | 1 | 1 | 3 | 0 | 0.03 |
| 7105 | Jeremy Russell | 1 | 1 | 3 | 0 | 0.03 |
| 7106 | Jermaine Gibbs | 1 | 1 | 3 | 0 | 0.03 |
| 7107 | Jerry Abbott | 1 | 1 | 3 | 0 | 0.03 |
| 7108 | Jessica Ward | 1 | 1 | 3 | 0 | 0.03 |
| 7109 | Jessica Wyatt | 1 | 1 | 3 | 0 | 0.03 |
| 7110 | Jesus Hatfield | 1 | 1 | 3 | 0 | 0.03 |
| 7111 | Jie Gong | 1 | 1 | 3 | 0 | 0.03 |
| 7112 | Jie Liao | 1 | 1 | 3 | 0 | 0.03 |
| 7113 | Jie Luo | 1 | 1 | 3 | 0 | 0.03 |
| 7114 | Jimmy Arnold | 1 | 1 | 3 | 0 | 0.03 |
| 7115 | Jing Hao | 1 | 1 | 3 | 0 | 0.03 |
| 7116 | Jing Peng | 1 | 1 | 3 | 0 | 0.03 |
| 7117 | Jing Tao | 1 | 1 | 3 | 0 | 0.03 |
| 7118 | Jivika Keer | 1 | 1 | 3 | 0 | 0.03 |
| 7119 | Jiya Raman | 1 | 1 | 3 | 0 | 0.03 |
| 7120 | Jody Jones | 1 | 1 | 3 | 0 | 0.03 |
| 7121 | Joel Foster | 1 | 1 | 3 | 0 | 0.03 |
| 7122 | Joerg Schleich | 1 | 1 | 3 | 0 | 0.03 |
| 7123 | Johannes Linke | 1 | 1 | 3 | 0 | 0.03 |
| 7124 | John Harris | 1 | 1 | 3 | 0 | 0.03 |
| 7125 | John May | 1 | 1 | 3 | 0 | 0.03 |
| 7126 | John Mcdonald | 1 | 1 | 3 | 0 | 0.03 |
| 7127 | John Rivera | 1 | 1 | 3 | 0 | 0.03 |
| 7128 | John Taylor | 1 | 1 | 3 | 0 | 0.03 |
| 7129 | John Watts | 1 | 1 | 3 | 0 | 0.03 |
| 7130 | John Wright | 1 | 1 | 3 | 0 | 0.03 |
| 7131 | Jonathan Barker | 1 | 1 | 3 | 0 | 0.03 |
| 7132 | Jonathan Oestrovsky | 1 | 1 | 3 | 0 | 0.03 |
| 7133 | Jordan Lutz | 1 | 1 | 3 | 0 | 0.03 |
| 7134 | Jose Cerdán Paniagua | 1 | 1 | 3 | 0 | 0.03 |
| 7135 | Jose Manuel Quintana Borrell | 1 | 1 | 3 | 0 | 0.03 |
| 7136 | Jose Martin | 1 | 1 | 3 | 0 | 0.03 |
| 7137 | Joseph Dillon | 1 | 1 | 3 | 0 | 0.03 |
| 7138 | Joseph Jones | 1 | 1 | 3 | 0 | 0.03 |
| 7139 | Joseph Moore | 1 | 1 | 3 | 0 | 0.03 |
| 7140 | Joseph Roman | 1 | 1 | 3 | 0 | 0.03 |
| 7141 | Joseph Stevens | 1 | 1 | 3 | 0 | 0.03 |
| 7142 | Joseph Thomas | 1 | 1 | 3 | 0 | 0.03 |
| 7143 | Joseph Villa | 1 | 1 | 3 | 0 | 0.03 |
| 7144 | Joshua Brewer | 1 | 1 | 3 | 0 | 0.03 |
| 7145 | Joshua Harris | 1 | 1 | 3 | 0 | 0.03 |
| 7146 | Joséphine Rodrigues | 1 | 1 | 3 | 0 | 0.03 |
| 7147 | Juan Shelton | 1 | 1 | 3 | 0 | 0.03 |
| 7148 | Julie Taylor | 1 | 1 | 3 | 0 | 0.03 |
| 7149 | Julita Kudełka | 1 | 1 | 3 | 0 | 0.03 |
| 7150 | Jun Zhao | 1 | 1 | 3 | 0 | 0.03 |
| 7151 | Justin Morales | 1 | 1 | 3 | 0 | 0.03 |
| 7152 | Kamil Bílek | 1 | 1 | 3 | 0 | 0.03 |
| 7153 | Kamil Sura | 1 | 1 | 3 | 0 | 0.03 |
| 7154 | Karl-Josef Reinhardt | 1 | 1 | 3 | 0 | 0.03 |
| 7155 | Kathleen Valentine | 1 | 1 | 3 | 0 | 0.03 |
| 7156 | Kathy Green | 1 | 1 | 3 | 0 | 0.03 |
| 7157 | Katie Fleming | 1 | 1 | 3 | 0 | 0.03 |
| 7158 | Katie Richards | 1 | 1 | 3 | 0 | 0.03 |
| 7159 | Kayla Jenkins | 1 | 1 | 3 | 0 | 0.03 |
| 7160 | Kayla Roberson | 1 | 1 | 3 | 0 | 0.03 |
| 7161 | Kazuya Kobayashi | 1 | 1 | 3 | 0 | 0.03 |
| 7162 | Kazuya Maeda | 1 | 1 | 3 | 0 | 0.03 |
| 7163 | Kazuya Matsumoto | 1 | 1 | 3 | 0 | 0.03 |
| 7164 | Kelli Mckinney | 1 | 1 | 3 | 0 | 0.03 |
| 7165 | Kelly Marshall | 1 | 1 | 3 | 0 | 0.03 |
| 7166 | Kelly Smith | 1 | 1 | 3 | 0 | 0.03 |
| 7167 | Kenneth Jimenez | 1 | 1 | 3 | 0 | 0.03 |
| 7168 | Kenneth Robinson | 1 | 1 | 3 | 0 | 0.03 |
| 7169 | Kenneth Ross | 1 | 1 | 3 | 0 | 0.03 |
| 7170 | Kevin Richardson | 1 | 1 | 3 | 0 | 0.03 |
| 7171 | Kimberly Campbell | 1 | 1 | 3 | 0 | 0.03 |
| 7172 | Kimberly Guerrero | 1 | 1 | 3 | 0 | 0.03 |
| 7173 | Kimberly Murphy | 1 | 1 | 3 | 0 | 0.03 |
| 7174 | Kimberly Thomas | 1 | 1 | 3 | 0 | 0.03 |
| 7175 | Kirk Kemp | 1 | 1 | 3 | 0 | 0.03 |
| 7176 | Kreszentia Staude | 1 | 1 | 3 | 0 | 0.03 |
| 7177 | Krista Collins | 1 | 1 | 3 | 0 | 0.03 |
| 7178 | Kristen Stanley | 1 | 1 | 3 | 0 | 0.03 |
| 7179 | Kristina Boyer | 1 | 1 | 3 | 0 | 0.03 |
| 7180 | Kristy Miller | 1 | 1 | 3 | 0 | 0.03 |
| 7181 | Kristy Olsen | 1 | 1 | 3 | 0 | 0.03 |
| 7182 | Laila Rosenow-Mans | 1 | 1 | 3 | 0 | 0.03 |
| 7183 | Lance Garcia | 1 | 1 | 3 | 0 | 0.03 |
| 7184 | Lando Parri | 1 | 1 | 3 | 0 | 0.03 |
| 7185 | Larry Miller | 1 | 1 | 3 | 0 | 0.03 |
| 7186 | Latasha Watts | 1 | 1 | 3 | 0 | 0.03 |
| 7187 | Lawrence Guzman | 1 | 1 | 3 | 0 | 0.03 |
| 7188 | Leah Moore | 1 | 1 | 3 | 0 | 0.03 |
| 7189 | Lei Hou | 1 | 1 | 3 | 0 | 0.03 |
| 7190 | Lei Meng | 1 | 1 | 3 | 0 | 0.03 |
| 7191 | Lei Ren | 1 | 1 | 3 | 0 | 0.03 |
| 7192 | Lei Song | 1 | 1 | 3 | 0 | 0.03 |
| 7193 | Leonard Suarez | 1 | 1 | 3 | 0 | 0.03 |
| 7194 | Li Meng | 1 | 1 | 3 | 0 | 0.03 |
| 7195 | Lindsay Ponce | 1 | 1 | 3 | 0 | 0.03 |
| 7196 | Lisa Baker | 1 | 1 | 3 | 0 | 0.03 |
| 7197 | Lisa Fuentes | 1 | 1 | 3 | 0 | 0.03 |
| 7198 | Lisa Hanna | 1 | 1 | 3 | 0 | 0.03 |
| 7199 | Lisa Kirk | 1 | 1 | 3 | 0 | 0.03 |
| 7200 | Lisa Mccoy | 1 | 1 | 3 | 0 | 0.03 |
| 7201 | Liwia Cygal | 1 | 1 | 3 | 0 | 0.03 |
| 7202 | Louis Herman | 1 | 1 | 3 | 0 | 0.03 |
| 7203 | Luc Hoarau | 1 | 1 | 3 | 0 | 0.03 |
| 7204 | Luca Gori-Visconti | 1 | 1 | 3 | 0 | 0.03 |
| 7205 | Luciano Calzada Arcos | 1 | 1 | 3 | 0 | 0.03 |
| 7206 | Luigina Fibonacci-Caruso | 1 | 1 | 3 | 0 | 0.03 |
| 7207 | Luisa Tommaseo | 1 | 1 | 3 | 0 | 0.03 |
| 7208 | Luke Payne | 1 | 1 | 3 | 0 | 0.03 |
| 7209 | Lupe Neira | 1 | 1 | 3 | 0 | 0.03 |
| 7210 | Mackenzie Murray | 1 | 1 | 3 | 0 | 0.03 |
| 7211 | Madeleine Raymond | 1 | 1 | 3 | 0 | 0.03 |
| 7212 | Madison Rodriguez | 1 | 1 | 3 | 0 | 0.03 |
| 7213 | Mahika Basu | 1 | 1 | 3 | 0 | 0.03 |
| 7214 | Manikya Toor | 1 | 1 | 3 | 0 | 0.03 |
| 7215 | Manjari Bobal | 1 | 1 | 3 | 0 | 0.03 |
| 7216 | Mannat Edwin | 1 | 1 | 3 | 0 | 0.03 |
| 7217 | Marcella Belletini | 1 | 1 | 3 | 0 | 0.03 |
| 7218 | Margherita Giammusso | 1 | 1 | 3 | 0 | 0.03 |
| 7219 | Margot Becker-Striebitz | 1 | 1 | 3 | 0 | 0.03 |
| 7220 | Maria Matthews | 1 | 1 | 3 | 0 | 0.03 |
| 7221 | Marie-Louise Wesack | 1 | 1 | 3 | 0 | 0.03 |
| 7222 | Marina Trapani | 1 | 1 | 3 | 0 | 0.03 |
| 7223 | Mariola Heser | 1 | 1 | 3 | 0 | 0.03 |
| 7224 | Martin Guilbert | 1 | 1 | 3 | 0 | 0.03 |
| 7225 | Marvin Heuser | 1 | 1 | 3 | 0 | 0.03 |
| 7226 | Mary Johnson | 1 | 1 | 3 | 0 | 0.03 |
| 7227 | Mary Walker | 1 | 1 | 3 | 0 | 0.03 |
| 7228 | Mary White | 1 | 1 | 3 | 0 | 0.03 |
| 7229 | Matthew Mitchell | 1 | 1 | 3 | 0 | 0.03 |
| 7230 | Matthäus Hendriks | 1 | 1 | 3 | 0 | 0.03 |
| 7231 | Megan Marsh | 1 | 1 | 3 | 0 | 0.03 |
| 7232 | Meike Döhn | 1 | 1 | 3 | 0 | 0.03 |
| 7233 | Melissa Watkins | 1 | 1 | 3 | 0 | 0.03 |
| 7234 | Mercedes Torlonia | 1 | 1 | 3 | 0 | 0.03 |
| 7235 | Michael Barry | 1 | 1 | 3 | 0 | 0.03 |
| 7236 | Michael Hayes | 1 | 1 | 3 | 0 | 0.03 |
| 7237 | Michael Johnson | 1 | 1 | 3 | 0 | 0.03 |
| 7238 | Michael Martin | 1 | 1 | 3 | 0 | 0.03 |
| 7239 | Michael Mccullough | 1 | 1 | 3 | 0 | 0.03 |
| 7240 | Michael Tapia | 1 | 1 | 3 | 0 | 0.03 |
| 7241 | Michael Watson | 1 | 1 | 3 | 0 | 0.03 |
| 7242 | Micheal Welch | 1 | 1 | 3 | 0 | 0.03 |
| 7243 | Michele Kim | 1 | 1 | 3 | 0 | 0.03 |
| 7244 | Michelle Gonzalez | 1 | 1 | 3 | 0 | 0.03 |
| 7245 | Michelle Johnson | 1 | 1 | 3 | 0 | 0.03 |
| 7246 | Miki Watanabe | 1 | 1 | 3 | 0 | 0.03 |
| 7247 | Milada Svobodová | 1 | 1 | 3 | 0 | 0.03 |
| 7248 | Milo Hendriks | 1 | 1 | 3 | 0 | 0.03 |
| 7249 | Miranda Robinson | 1 | 1 | 3 | 0 | 0.03 |
| 7250 | Miss Cynthia Myers | 1 | 1 | 3 | 0 | 0.03 |
| 7251 | Mitchell Sharp | 1 | 1 | 3 | 0 | 0.03 |
| 7252 | Mojmír Hruška | 1 | 1 | 3 | 0 | 0.03 |
| 7253 | Monica Blevins | 1 | 1 | 3 | 0 | 0.03 |
| 7254 | Monica Murphy | 1 | 1 | 3 | 0 | 0.03 |
| 7255 | Monica Ramirez | 1 | 1 | 3 | 0 | 0.03 |
| 7256 | Morgan Carlson | 1 | 1 | 3 | 0 | 0.03 |
| 7257 | Morgan Shelton | 1 | 1 | 3 | 0 | 0.03 |
| 7258 | Moritz Keudel | 1 | 1 | 3 | 0 | 0.03 |
| 7259 | Nakul Gole | 1 | 1 | 3 | 0 | 0.03 |
| 7260 | Naoto Suzuki | 1 | 1 | 3 | 0 | 0.03 |
| 7261 | Nath Henry | 1 | 1 | 3 | 0 | 0.03 |
| 7262 | Nathan Nelson | 1 | 1 | 3 | 0 | 0.03 |
| 7263 | Nayantara Dugal | 1 | 1 | 3 | 0 | 0.03 |
| 7264 | Nicholas Gonzalez | 1 | 1 | 3 | 0 | 0.03 |
| 7265 | Nicholas Mckinney | 1 | 1 | 3 | 0 | 0.03 |
| 7266 | Nicholas Morgan | 1 | 1 | 3 | 0 | 0.03 |
| 7267 | Nino Veneziano | 1 | 1 | 3 | 0 | 0.03 |
| 7268 | Nirvaan Thaker | 1 | 1 | 3 | 0 | 0.03 |
| 7269 | Odette Dupuy | 1 | 1 | 3 | 0 | 0.03 |
| 7270 | Omnira | 1 | 1 | 3 | 0 | 0.03 |
| 7271 | Osamu Yamashita | 1 | 1 | 3 | 0 | 0.03 |
| 7272 | Oto Macháček | 1 | 1 | 3 | 0 | 0.03 |
| 7273 | Paloma Fogazzaro | 1 | 1 | 3 | 0 | 0.03 |
| 7274 | Pamela Ayala | 1 | 1 | 3 | 0 | 0.03 |
| 7275 | Pamela Elliott | 1 | 1 | 3 | 0 | 0.03 |
| 7276 | Pamela Massey | 1 | 1 | 3 | 0 | 0.03 |
| 7277 | Parinaaz Deshmukh | 1 | 1 | 3 | 0 | 0.03 |
| 7278 | Pascal Pärtzelt-Jockel | 1 | 1 | 3 | 0 | 0.03 |
| 7279 | Patrick Williams | 1 | 1 | 3 | 0 | 0.03 |
| 7280 | Paweł Gęca | 1 | 1 | 3 | 0 | 0.03 |
| 7281 | Peter Knapp | 1 | 1 | 3 | 0 | 0.03 |
| 7282 | Philip George | 1 | 1 | 3 | 0 | 0.03 |
| 7283 | Pia Schleich | 1 | 1 | 3 | 0 | 0.03 |
| 7284 | Pina Garrone | 1 | 1 | 3 | 0 | 0.03 |
| 7285 | Ping Yang | 1 | 1 | 3 | 0 | 0.03 |
| 7286 | Rachel Garcia | 1 | 1 | 3 | 0 | 0.03 |
| 7287 | Rafael Hoz Pizarro | 1 | 1 | 3 | 0 | 0.03 |
| 7288 | Ralph Bell | 1 | 1 | 3 | 0 | 0.03 |
| 7289 | Rania Chadha | 1 | 1 | 3 | 0 | 0.03 |
| 7290 | Raunak Rana | 1 | 1 | 3 | 0 | 0.03 |
| 7291 | Raymond Hornich-Jacob | 1 | 1 | 3 | 0 | 0.03 |
| 7292 | Raymond Robinson | 1 | 1 | 3 | 0 | 0.03 |
| 7293 | Rebecca Schultz | 1 | 1 | 3 | 0 | 0.03 |
| 7294 | Regina Beck | 1 | 1 | 3 | 0 | 0.03 |
| 7295 | Rei Sato | 1 | 1 | 3 | 0 | 0.03 |
| 7296 | Renee Walker | 1 | 1 | 3 | 0 | 0.03 |
| 7297 | Renske Godfrey van Alemannië | 1 | 1 | 3 | 0 | 0.03 |
| 7298 | Renée Bègue-Giraud | 1 | 1 | 3 | 0 | 0.03 |
| 7299 | Rhythm Collective | 1 | 1 | 3 | 0 | 0.03 |
| 7300 | Richard Francis | 1 | 1 | 3 | 0 | 0.03 |
| 7301 | Richard Moore | 1 | 1 | 3 | 0 | 0.03 |
| 7302 | Ricky Richards | 1 | 1 | 3 | 0 | 0.03 |
| 7303 | Robert Chen | 1 | 1 | 3 | 0 | 0.03 |
| 7304 | Robert Jefferson | 1 | 1 | 3 | 0 | 0.03 |
| 7305 | Robert Ryan | 1 | 1 | 3 | 0 | 0.03 |
| 7306 | Robin Cline | 1 | 1 | 3 | 0 | 0.03 |
| 7307 | Robin Mayer | 1 | 1 | 3 | 0 | 0.03 |
| 7308 | Rodolfo Montecchi-Bonomo | 1 | 1 | 3 | 0 | 0.03 |
| 7309 | Roman Doria | 1 | 1 | 3 | 0 | 0.03 |
| 7310 | Rosalinde Kreusel-Mühle | 1 | 1 | 3 | 0 | 0.03 |
| 7311 | Roy Tran | 1 | 1 | 3 | 0 | 0.03 |
| 7312 | Ruben Watkins | 1 | 1 | 3 | 0 | 0.03 |
| 7313 | Ryan Morales | 1 | 1 | 3 | 0 | 0.03 |
| 7314 | Ryan Osborn | 1 | 1 | 3 | 0 | 0.03 |
| 7315 | Rémy Jourdan | 1 | 1 | 3 | 0 | 0.03 |
| 7316 | Sabrina Marquez | 1 | 1 | 3 | 0 | 0.03 |
| 7317 | Saksham Borra | 1 | 1 | 3 | 0 | 0.03 |
| 7318 | Sandra Miller | 1 | 1 | 3 | 0 | 0.03 |
| 7319 | Sara Laszuk | 1 | 1 | 3 | 0 | 0.03 |
| 7320 | Sarah Caldwell | 1 | 1 | 3 | 0 | 0.03 |
| 7321 | Sarah Riley | 1 | 1 | 3 | 0 | 0.03 |
| 7322 | Sarah Sims | 1 | 1 | 3 | 0 | 0.03 |
| 7323 | Savannah Leblanc | 1 | 1 | 3 | 0 | 0.03 |
| 7324 | Scott Nichols | 1 | 1 | 3 | 0 | 0.03 |
| 7325 | Scott Schwartz | 1 | 1 | 3 | 0 | 0.03 |
| 7326 | Selena Gonzalez | 1 | 1 | 3 | 0 | 0.03 |
| 7327 | Shane Alexander | 1 | 1 | 3 | 0 | 0.03 |
| 7328 | Shannon Jacobson | 1 | 1 | 3 | 0 | 0.03 |
| 7329 | Sharon Mitchell | 1 | 1 | 3 | 0 | 0.03 |
| 7330 | Sheena Lane | 1 | 1 | 3 | 0 | 0.03 |
| 7331 | Sheila Flores | 1 | 1 | 3 | 0 | 0.03 |
| 7332 | Sherry Bell | 1 | 1 | 3 | 0 | 0.03 |
| 7333 | Sherry Mcdaniel | 1 | 1 | 3 | 0 | 0.03 |
| 7334 | Stacy Moore | 1 | 1 | 3 | 0 | 0.03 |
| 7335 | Stanislav Prokop | 1 | 1 | 3 | 0 | 0.03 |
| 7336 | Stephanie Fowler | 1 | 1 | 3 | 0 | 0.03 |
| 7337 | Stephanie Gray | 1 | 1 | 3 | 0 | 0.03 |
| 7338 | Stephen Santiago | 1 | 1 | 3 | 0 | 0.03 |
| 7339 | Steve Bailey | 1 | 1 | 3 | 0 | 0.03 |
| 7340 | Steven Berg | 1 | 1 | 3 | 0 | 0.03 |
| 7341 | Steven Weaver | 1 | 1 | 3 | 0 | 0.03 |
| 7342 | Summer Mahoney | 1 | 1 | 3 | 0 | 0.03 |
| 7343 | Susan Francis | 1 | 1 | 3 | 0 | 0.03 |
| 7344 | Susan Randall | 1 | 1 | 3 | 0 | 0.03 |
| 7345 | Susan Rodriguez | 1 | 1 | 3 | 0 | 0.03 |
| 7346 | Susanna Raimondi | 1 | 1 | 3 | 0 | 0.03 |
| 7347 | Suzanne Martinez | 1 | 1 | 3 | 0 | 0.03 |
| 7348 | Tammy Campos | 1 | 1 | 3 | 0 | 0.03 |
| 7349 | Tammy Howell | 1 | 1 | 3 | 0 | 0.03 |
| 7350 | Tao Zhong | 1 | 1 | 3 | 0 | 0.03 |
| 7351 | Taro Mori | 1 | 1 | 3 | 0 | 0.03 |
| 7352 | Taro Sakamoto | 1 | 1 | 3 | 0 | 0.03 |
| 7353 | Tatjana Gieß | 1 | 1 | 3 | 0 | 0.03 |
| 7354 | Taylor Hayes | 1 | 1 | 3 | 0 | 0.03 |
| 7355 | Taylor Martin | 1 | 1 | 3 | 0 | 0.03 |
| 7356 | Teresa Nelson | 1 | 1 | 3 | 0 | 0.03 |
| 7357 | Terry Adams | 1 | 1 | 3 | 0 | 0.03 |
| 7358 | Theodore Simmons | 1 | 1 | 3 | 0 | 0.03 |
| 7359 | Theresa Johnson | 1 | 1 | 3 | 0 | 0.03 |
| 7360 | Thomas Meyer | 1 | 1 | 3 | 0 | 0.03 |
| 7361 | Tim Morgan | 1 | 1 | 3 | 0 | 0.03 |
| 7362 | Timothy Sanders | 1 | 1 | 3 | 0 | 0.03 |
| 7363 | Timothée Charles | 1 | 1 | 3 | 0 | 0.03 |
| 7364 | Tina Hart | 1 | 1 | 3 | 0 | 0.03 |
| 7365 | Tina Morgan | 1 | 1 | 3 | 0 | 0.03 |
| 7366 | Tina Spencer | 1 | 1 | 3 | 0 | 0.03 |
| 7367 | Todd Thompson | 1 | 1 | 3 | 0 | 0.03 |
| 7368 | Tonya May | 1 | 1 | 3 | 0 | 0.03 |
| 7369 | Tonya Wright | 1 | 1 | 3 | 0 | 0.03 |
| 7370 | Travis Price | 1 | 1 | 3 | 0 | 0.03 |
| 7371 | Trevor Singh | 1 | 1 | 3 | 0 | 0.03 |
| 7372 | Tyler Case | 1 | 1 | 3 | 0 | 0.03 |
| 7373 | Tyler Clay | 1 | 1 | 3 | 0 | 0.03 |
| 7374 | Ulrich Klotz | 1 | 1 | 3 | 0 | 0.03 |
| 7375 | Valerie Pena | 1 | 1 | 3 | 0 | 0.03 |
| 7376 | Valérie Valette | 1 | 1 | 3 | 0 | 0.03 |
| 7377 | Vicenta Castañeda Arroyo | 1 | 1 | 3 | 0 | 0.03 |
| 7378 | Victoria Velazquez | 1 | 1 | 3 | 0 | 0.03 |
| 7379 | Wei Ren | 1 | 1 | 3 | 0 | 0.03 |
| 7380 | Wei Yan | 1 | 1 | 3 | 0 | 0.03 |
| 7381 | Wendy Nelson | 1 | 1 | 3 | 0 | 0.03 |
| 7382 | Whitney Schmidt | 1 | 1 | 3 | 0 | 0.03 |
| 7383 | William Delacruz | 1 | 1 | 3 | 0 | 0.03 |
| 7384 | William Francis | 1 | 1 | 3 | 0 | 0.03 |
| 7385 | William Shields | 1 | 1 | 3 | 0 | 0.03 |
| 7386 | Wolfgang Bärer-Holt | 1 | 1 | 3 | 0 | 0.03 |
| 7387 | Xavier Baron | 1 | 1 | 3 | 0 | 0.03 |
| 7388 | Xiuying Feng | 1 | 1 | 3 | 0 | 0.03 |
| 7389 | Xiuying Zhao | 1 | 1 | 3 | 0 | 0.03 |
| 7390 | Yan Jiang | 1 | 1 | 3 | 0 | 0.03 |
| 7391 | Yan Lai | 1 | 1 | 3 | 0 | 0.03 |
| 7392 | Yan Yi | 1 | 1 | 3 | 0 | 0.03 |
| 7393 | Yang Qian | 1 | 1 | 3 | 0 | 0.03 |
| 7394 | Yang Xia | 1 | 1 | 3 | 0 | 0.03 |
| 7395 | Yashvi Bahri | 1 | 1 | 3 | 0 | 0.03 |
| 7396 | Yolanda Lee | 1 | 1 | 3 | 0 | 0.03 |
| 7397 | Yong Jiang | 1 | 1 | 3 | 0 | 0.03 |
| 7398 | Yong Xiao | 1 | 1 | 3 | 0 | 0.03 |
| 7399 | Yvette Cohen | 1 | 1 | 3 | 0 | 0.03 |
| 7400 | Yvonne Mullins | 1 | 1 | 3 | 0 | 0.03 |
| 7401 | Zachary Wells | 1 | 1 | 3 | 0 | 0.03 |
| 7402 | Zara Kibe | 1 | 1 | 3 | 0 | 0.03 |
| 7403 | Zbigniew Stey | 1 | 1 | 3 | 0 | 0.03 |
| 7404 | Frau Viola Ullmann | 1 | 0 | 12 | 2 | 0.03 |
| 7405 | Ivona Žáková | 1 | 0 | 12 | 2 | 0.03 |
| 7406 | Thies Seifert | 1 | 0 | 12 | 2 | 0.03 |
| 7407 | Cole Pierce | 2 | 0 | 3 | 0 | 0.03 |
| 7408 | Holden Rhys | 2 | 0 | 3 | 0 | 0.03 |
| 7409 | Max Everhart | 2 | 0 | 3 | 0 | 0.03 |
| 7410 | Abigail Scott | 1 | 1 | 2 | 0 | 0.03 |
| 7411 | Abram Kala | 1 | 1 | 2 | 0 | 0.03 |
| 7412 | Adam Fletcher | 1 | 1 | 2 | 0 | 0.03 |
| 7413 | Adam Kroker | 1 | 1 | 2 | 0 | 0.03 |
| 7414 | Adrianna Panasiewicz | 1 | 1 | 2 | 0 | 0.03 |
| 7415 | Advika Tailor | 1 | 1 | 2 | 0 | 0.03 |
| 7416 | Adélaïde Letellier de Cordier | 1 | 1 | 2 | 0 | 0.03 |
| 7417 | Agata Bähr-Metz | 1 | 1 | 2 | 0 | 0.03 |
| 7418 | Ahana Babu | 1 | 1 | 2 | 0 | 0.03 |
| 7419 | Alessandro Zito | 1 | 1 | 2 | 0 | 0.03 |
| 7420 | Alexa Adolph | 1 | 1 | 2 | 0 | 0.03 |
| 7421 | Alexis Hart | 1 | 1 | 2 | 0 | 0.03 |
| 7422 | Alf Bähr | 1 | 1 | 2 | 0 | 0.03 |
| 7423 | Alisha Fernandez | 1 | 1 | 2 | 0 | 0.03 |
| 7424 | Allison Williams | 1 | 1 | 2 | 0 | 0.03 |
| 7425 | Amanda Cole | 1 | 1 | 2 | 0 | 0.03 |
| 7426 | Anahi Buch | 1 | 1 | 2 | 0 | 0.03 |
| 7427 | Andrea White | 1 | 1 | 2 | 0 | 0.03 |
| 7428 | Andree Dippel | 1 | 1 | 2 | 0 | 0.03 |
| 7429 | Andree Tschentscher | 1 | 1 | 2 | 0 | 0.03 |
| 7430 | Andrew Carrillo | 1 | 1 | 2 | 0 | 0.03 |
| 7431 | Angel Mccullough | 1 | 1 | 2 | 0 | 0.03 |
| 7432 | Anna Woodard | 1 | 1 | 2 | 0 | 0.03 |
| 7433 | Annetta Fanucci | 1 | 1 | 2 | 0 | 0.03 |
| 7434 | Ashley Powers | 1 | 1 | 2 | 0 | 0.03 |
| 7435 | Astrid Weinhold | 1 | 1 | 2 | 0 | 0.03 |
| 7436 | Aurore Leroux | 1 | 1 | 2 | 0 | 0.03 |
| 7437 | Austin Adams | 1 | 1 | 2 | 0 | 0.03 |
| 7438 | Barbara Russell | 1 | 1 | 2 | 0 | 0.03 |
| 7439 | Belén de Trillo | 1 | 1 | 2 | 0 | 0.03 |
| 7440 | Betty Vega | 1 | 1 | 2 | 0 | 0.03 |
| 7441 | Bhamini Luthra | 1 | 1 | 2 | 0 | 0.03 |
| 7442 | Božena Dušková | 1 | 1 | 2 | 0 | 0.03 |
| 7443 | Bradley Reeves Jr. | 1 | 1 | 2 | 0 | 0.03 |
| 7444 | Brady Brown | 1 | 1 | 2 | 0 | 0.03 |
| 7445 | Brandon Horton | 1 | 1 | 2 | 0 | 0.03 |
| 7446 | Brandy Chung PhD | 1 | 1 | 2 | 0 | 0.03 |
| 7447 | Brett Bond | 1 | 1 | 2 | 0 | 0.03 |
| 7448 | Brett Whitehead | 1 | 1 | 2 | 0 | 0.03 |
| 7449 | Brian Melton | 1 | 1 | 2 | 0 | 0.03 |
| 7450 | Brian Mitchell | 1 | 1 | 2 | 0 | 0.03 |
| 7451 | Brian Moody | 1 | 1 | 2 | 0 | 0.03 |
| 7452 | Brian Price | 1 | 1 | 2 | 0 | 0.03 |
| 7453 | Brittany Horn | 1 | 1 | 2 | 0 | 0.03 |
| 7454 | Bruce Hernandez | 1 | 1 | 2 | 0 | 0.03 |
| 7455 | Bryan Hale | 1 | 1 | 2 | 0 | 0.03 |
| 7456 | Candace Anderson | 1 | 1 | 2 | 0 | 0.03 |
| 7457 | Capucine Martin | 1 | 1 | 2 | 0 | 0.03 |
| 7458 | Cas Everde | 1 | 1 | 2 | 0 | 0.03 |
| 7459 | Catalina Borja Barbero | 1 | 1 | 2 | 0 | 0.03 |
| 7460 | Catherine Mcdonald | 1 | 1 | 2 | 0 | 0.03 |
| 7461 | Cecilia Parejo Carrillo | 1 | 1 | 2 | 0 | 0.03 |
| 7462 | Cecilia Scholz | 1 | 1 | 2 | 0 | 0.03 |
| 7463 | Chantal Gomes | 1 | 1 | 2 | 0 | 0.03 |
| 7464 | Chantal-Geneviève Fournier | 1 | 1 | 2 | 0 | 0.03 |
| 7465 | Chao Mo | 1 | 1 | 2 | 0 | 0.03 |
| 7466 | Charles Jordan | 1 | 1 | 2 | 0 | 0.03 |
| 7467 | Charles Norman | 1 | 1 | 2 | 0 | 0.03 |
| 7468 | Charles Smith | 1 | 1 | 2 | 0 | 0.03 |
| 7469 | Charles Spears | 1 | 1 | 2 | 0 | 0.03 |
| 7470 | Charlotte Marchand | 1 | 1 | 2 | 0 | 0.03 |
| 7471 | Charvi Taneja | 1 | 1 | 2 | 0 | 0.03 |
| 7472 | Cheryl Wiley | 1 | 1 | 2 | 0 | 0.03 |
| 7473 | Chiyo Ota | 1 | 1 | 2 | 0 | 0.03 |
| 7474 | Christina Dalton | 1 | 1 | 2 | 0 | 0.03 |
| 7475 | Christine Mendoza | 1 | 1 | 2 | 0 | 0.03 |
| 7476 | Christopher Hardy | 1 | 1 | 2 | 0 | 0.03 |
| 7477 | Christopher Martin | 1 | 1 | 2 | 0 | 0.03 |
| 7478 | Claude Jean | 1 | 1 | 2 | 0 | 0.03 |
| 7479 | Cody Mathis | 1 | 1 | 2 | 0 | 0.03 |
| 7480 | Corey Ramirez | 1 | 1 | 2 | 0 | 0.03 |
| 7481 | Corinne Leleu | 1 | 1 | 2 | 0 | 0.03 |
| 7482 | Curt Wieloch | 1 | 1 | 2 | 0 | 0.03 |
| 7483 | Cynthia Hoover | 1 | 1 | 2 | 0 | 0.03 |
| 7484 | Cyprian Perczak | 1 | 1 | 2 | 0 | 0.03 |
| 7485 | Dale Bell | 1 | 1 | 2 | 0 | 0.03 |
| 7486 | Damini Wable | 1 | 1 | 2 | 0 | 0.03 |
| 7487 | Daniel Watson | 1 | 1 | 2 | 0 | 0.03 |
| 7488 | Danielle Moore | 1 | 1 | 2 | 0 | 0.03 |
| 7489 | Dariusz Madera | 1 | 1 | 2 | 0 | 0.03 |
| 7490 | Darshit Chopra | 1 | 1 | 2 | 0 | 0.03 |
| 7491 | David Gibson | 1 | 1 | 2 | 0 | 0.03 |
| 7492 | David Singleton | 1 | 1 | 2 | 0 | 0.03 |
| 7493 | David Sloan | 1 | 1 | 2 | 0 | 0.03 |
| 7494 | Dawn Kelly | 1 | 1 | 2 | 0 | 0.03 |
| 7495 | Debra Wolfe | 1 | 1 | 2 | 0 | 0.03 |
| 7496 | Derrick Scott | 1 | 1 | 2 | 0 | 0.03 |
| 7497 | Devansh Bakshi | 1 | 1 | 2 | 0 | 0.03 |
| 7498 | Divit Behl | 1 | 1 | 2 | 0 | 0.03 |
| 7499 | Donna Ellison | 1 | 1 | 2 | 0 | 0.03 |
| 7500 | Douglas Roberts | 1 | 1 | 2 | 0 | 0.03 |
| 7501 | Dustin Smith | 1 | 1 | 2 | 0 | 0.03 |
| 7502 | Edith Schaaf | 1 | 1 | 2 | 0 | 0.03 |
| 7503 | Edward Collier | 1 | 1 | 2 | 0 | 0.03 |
| 7504 | Edward Kirby | 1 | 1 | 2 | 0 | 0.03 |
| 7505 | Edward Kraushaar | 1 | 1 | 2 | 0 | 0.03 |
| 7506 | Elizabeth Mccann | 1 | 1 | 2 | 0 | 0.03 |
| 7507 | Elladio Badoer-Beccaria | 1 | 1 | 2 | 0 | 0.03 |
| 7508 | Emily Arnold | 1 | 1 | 2 | 0 | 0.03 |
| 7509 | Emily Werner | 1 | 1 | 2 | 0 | 0.03 |
| 7510 | Emin Mentzel | 1 | 1 | 2 | 0 | 0.03 |
| 7511 | Emma Ruiz | 1 | 1 | 2 | 0 | 0.03 |
| 7512 | Erica Shaffer | 1 | 1 | 2 | 0 | 0.03 |
| 7513 | Erika Nguyen | 1 | 1 | 2 | 0 | 0.03 |
| 7514 | Eshani Deep | 1 | 1 | 2 | 0 | 0.03 |
| 7515 | Eugene Powell | 1 | 1 | 2 | 0 | 0.03 |
| 7516 | Eugenie Scheel | 1 | 1 | 2 | 0 | 0.03 |
| 7517 | Evangelina Bautista Catalá | 1 | 1 | 2 | 0 | 0.03 |
| 7518 | Evi Dietz | 1 | 1 | 2 | 0 | 0.03 |
| 7519 | Fang Cai | 1 | 1 | 2 | 0 | 0.03 |
| 7520 | Farhan Seshadri | 1 | 1 | 2 | 0 | 0.03 |
| 7521 | Fenne Ferran | 1 | 1 | 2 | 0 | 0.03 |
| 7522 | Frank Green | 1 | 1 | 2 | 0 | 0.03 |
| 7523 | Frau Oxana Jüttner | 1 | 1 | 2 | 0 | 0.03 |
| 7524 | Frau Raphaela Bohnbach | 1 | 1 | 2 | 0 | 0.03 |
| 7525 | Friedrich Eberhardt | 1 | 1 | 2 | 0 | 0.03 |
| 7526 | Gaetano Hartmann | 1 | 1 | 2 | 0 | 0.03 |
| 7527 | George Lloyd | 1 | 1 | 2 | 0 | 0.03 |
| 7528 | Georges Delorme | 1 | 1 | 2 | 0 | 0.03 |
| 7529 | Gerald Shepherd | 1 | 1 | 2 | 0 | 0.03 |
| 7530 | Gina Lehmann-Süßebier | 1 | 1 | 2 | 0 | 0.03 |
| 7531 | Goffredo Cheda | 1 | 1 | 2 | 0 | 0.03 |
| 7532 | Graciana Sacristán Saura | 1 | 1 | 2 | 0 | 0.03 |
| 7533 | Gregory Morris | 1 | 1 | 2 | 0 | 0.03 |
| 7534 | Grzegorz Pacocha | 1 | 1 | 2 | 0 | 0.03 |
| 7535 | Gudrun Atzler | 1 | 1 | 2 | 0 | 0.03 |
| 7536 | Guiying Luo | 1 | 1 | 2 | 0 | 0.03 |
| 7537 | Hailey Andrews | 1 | 1 | 2 | 0 | 0.03 |
| 7538 | Hanne Kambs | 1 | 1 | 2 | 0 | 0.03 |
| 7539 | Hans-Jörg Lehmann | 1 | 1 | 2 | 0 | 0.03 |
| 7540 | Harriet Wilms-Segebahn | 1 | 1 | 2 | 0 | 0.03 |
| 7541 | Harro Gerlach | 1 | 1 | 2 | 0 | 0.03 |
| 7542 | Haruka Kobayashi | 1 | 1 | 2 | 0 | 0.03 |
| 7543 | Heather Hanna | 1 | 1 | 2 | 0 | 0.03 |
| 7544 | Heather Hardy | 1 | 1 | 2 | 0 | 0.03 |
| 7545 | Heidi Perez | 1 | 1 | 2 | 0 | 0.03 |
| 7546 | Heidi Smith | 1 | 1 | 2 | 0 | 0.03 |
| 7547 | Helene van der Dussen | 1 | 1 | 2 | 0 | 0.03 |
| 7548 | Henri Da Costa | 1 | 1 | 2 | 0 | 0.03 |
| 7549 | Henri Maillard | 1 | 1 | 2 | 0 | 0.03 |
| 7550 | Herr Heinz-Gerd Schleich | 1 | 1 | 2 | 0 | 0.03 |
| 7551 | Hilmar Budig-Seip | 1 | 1 | 2 | 0 | 0.03 |
| 7552 | Himmat Shroff | 1 | 1 | 2 | 0 | 0.03 |
| 7553 | Hiroshi Yamamoto | 1 | 1 | 2 | 0 | 0.03 |
| 7554 | Holger Trupp | 1 | 1 | 2 | 0 | 0.03 |
| 7555 | Honoré Leduc | 1 | 1 | 2 | 0 | 0.03 |
| 7556 | Honoré-Alexandre Vidal | 1 | 1 | 2 | 0 | 0.03 |
| 7557 | Howard Taylor | 1 | 1 | 2 | 0 | 0.03 |
| 7558 | Hunter Green | 1 | 1 | 2 | 0 | 0.03 |
| 7559 | Ian Santos | 1 | 1 | 2 | 0 | 0.03 |
| 7560 | Ildefonso Aragón Guerra | 1 | 1 | 2 | 0 | 0.03 |
| 7561 | Imelda Reising-Franke | 1 | 1 | 2 | 0 | 0.03 |
| 7562 | Isaac Huet du Cousin | 1 | 1 | 2 | 0 | 0.03 |
| 7563 | Isaiah Morales | 1 | 1 | 2 | 0 | 0.03 |
| 7564 | Jafet Páez-Montenegro | 1 | 1 | 2 | 0 | 0.03 |
| 7565 | James Beard | 1 | 1 | 2 | 0 | 0.03 |
| 7566 | James Ellis | 1 | 1 | 2 | 0 | 0.03 |
| 7567 | James George | 1 | 1 | 2 | 0 | 0.03 |
| 7568 | James Hopkins | 1 | 1 | 2 | 0 | 0.03 |
| 7569 | James Li | 1 | 1 | 2 | 0 | 0.03 |
| 7570 | James Odom | 1 | 1 | 2 | 0 | 0.03 |
| 7571 | Jamie Castro | 1 | 1 | 2 | 0 | 0.03 |
| 7572 | Janet Aguilar | 1 | 1 | 2 | 0 | 0.03 |
| 7573 | Janet Hunter | 1 | 1 | 2 | 0 | 0.03 |
| 7574 | Janin Hartmann | 1 | 1 | 2 | 0 | 0.03 |
| 7575 | Jason Ali | 1 | 1 | 2 | 0 | 0.03 |
| 7576 | Jason Robles | 1 | 1 | 2 | 0 | 0.03 |
| 7577 | Jason Vaughn | 1 | 1 | 2 | 0 | 0.03 |
| 7578 | Jeanette Carey | 1 | 1 | 2 | 0 | 0.03 |
| 7579 | Jeanette Wagner | 1 | 1 | 2 | 0 | 0.03 |
| 7580 | Jennifer Tate | 1 | 1 | 2 | 0 | 0.03 |
| 7581 | Jeremi Głuszko | 1 | 1 | 2 | 0 | 0.03 |
| 7582 | Jeremi Piórek | 1 | 1 | 2 | 0 | 0.03 |
| 7583 | Jessica Esparza | 1 | 1 | 2 | 0 | 0.03 |
| 7584 | Jhanvi Krishnamurthy | 1 | 1 | 2 | 0 | 0.03 |
| 7585 | Jie Hou | 1 | 1 | 2 | 0 | 0.03 |
| 7586 | Jie Peng | 1 | 1 | 2 | 0 | 0.03 |
| 7587 | Jie Qiu | 1 | 1 | 2 | 0 | 0.03 |
| 7588 | Jill Smith | 1 | 1 | 2 | 0 | 0.03 |
| 7589 | John Buchanan | 1 | 1 | 2 | 0 | 0.03 |
| 7590 | John Maldonado | 1 | 1 | 2 | 0 | 0.03 |
| 7591 | Jonathan Jones Jr. | 1 | 1 | 2 | 0 | 0.03 |
| 7592 | Jordan Hopkins | 1 | 1 | 2 | 0 | 0.03 |
| 7593 | Joseph Escobar | 1 | 1 | 2 | 0 | 0.03 |
| 7594 | Joseph Hart | 1 | 1 | 2 | 0 | 0.03 |
| 7595 | Joseph Whitaker | 1 | 1 | 2 | 0 | 0.03 |
| 7596 | Jules Lemonnier | 1 | 1 | 2 | 0 | 0.03 |
| 7597 | Julia Berry | 1 | 1 | 2 | 0 | 0.03 |
| 7598 | Julia Davis | 1 | 1 | 2 | 0 | 0.03 |
| 7599 | Julie Gonzalez | 1 | 1 | 2 | 0 | 0.03 |
| 7600 | Julie Griffin | 1 | 1 | 2 | 0 | 0.03 |
| 7601 | Julie Nielsen | 1 | 1 | 2 | 0 | 0.03 |
| 7602 | Julie Thomas | 1 | 1 | 2 | 0 | 0.03 |
| 7603 | Jun Zhong | 1 | 1 | 2 | 0 | 0.03 |
| 7604 | Kaitlyn Brown | 1 | 1 | 2 | 0 | 0.03 |
| 7605 | Kaitlyn Castaneda PhD | 1 | 1 | 2 | 0 | 0.03 |
| 7606 | Kamila Bobko | 1 | 1 | 2 | 0 | 0.03 |
| 7607 | Karl Bruder | 1 | 1 | 2 | 0 | 0.03 |
| 7608 | Karla Moreno | 1 | 1 | 2 | 0 | 0.03 |
| 7609 | Katelyn Malone | 1 | 1 | 2 | 0 | 0.03 |
| 7610 | Katherine Tanner | 1 | 1 | 2 | 0 | 0.03 |
| 7611 | Kathleen Fowler | 1 | 1 | 2 | 0 | 0.03 |
| 7612 | Katy Spieß | 1 | 1 | 2 | 0 | 0.03 |
| 7613 | Kayla Martinez | 1 | 1 | 2 | 0 | 0.03 |
| 7614 | Kelly Barrett | 1 | 1 | 2 | 0 | 0.03 |
| 7615 | Kelly Clayton | 1 | 1 | 2 | 0 | 0.03 |
| 7616 | Kenneth Hall | 1 | 1 | 2 | 0 | 0.03 |
| 7617 | Kenneth Lopez | 1 | 1 | 2 | 0 | 0.03 |
| 7618 | Kevin Thomas | 1 | 1 | 2 | 0 | 0.03 |
| 7619 | Kimberly Porter | 1 | 1 | 2 | 0 | 0.03 |
| 7620 | Klaus-Werner Löchel | 1 | 1 | 2 | 0 | 0.03 |
| 7621 | Kristin Shepard | 1 | 1 | 2 | 0 | 0.03 |
| 7622 | Krystal Reese | 1 | 1 | 2 | 0 | 0.03 |
| 7623 | Kyle Lawrence | 1 | 1 | 2 | 0 | 0.03 |
| 7624 | Larry Bailey | 1 | 1 | 2 | 0 | 0.03 |
| 7625 | Laura Carson | 1 | 1 | 2 | 0 | 0.03 |
| 7626 | Laurie Anderson | 1 | 1 | 2 | 0 | 0.03 |
| 7627 | Lei Chang | 1 | 1 | 2 | 0 | 0.03 |
| 7628 | Lei Dong | 1 | 1 | 2 | 0 | 0.03 |
| 7629 | Lei Xu | 1 | 1 | 2 | 0 | 0.03 |
| 7630 | Li Cao | 1 | 1 | 2 | 0 | 0.03 |
| 7631 | Li Su | 1 | 1 | 2 | 0 | 0.03 |
| 7632 | Lidia Dörschner-Käster | 1 | 1 | 2 | 0 | 0.03 |
| 7633 | Linda Bailey | 1 | 1 | 2 | 0 | 0.03 |
| 7634 | Liwia Mitera | 1 | 1 | 2 | 0 | 0.03 |
| 7635 | Loredana Bertolucci | 1 | 1 | 2 | 0 | 0.03 |
| 7636 | Loretta Börner | 1 | 1 | 2 | 0 | 0.03 |
| 7637 | Lori Montgomery | 1 | 1 | 2 | 0 | 0.03 |
| 7638 | Léon Lemaire | 1 | 1 | 2 | 0 | 0.03 |
| 7639 | Maaya Hayashi | 1 | 1 | 2 | 0 | 0.03 |
| 7640 | Maaya Suzuki | 1 | 1 | 2 | 0 | 0.03 |
| 7641 | Madeline Gentry | 1 | 1 | 2 | 0 | 0.03 |
| 7642 | Manjari Varty | 1 | 1 | 2 | 0 | 0.03 |
| 7643 | Manuel Morrison | 1 | 1 | 2 | 0 | 0.03 |
| 7644 | Mar Abril Balaguer | 1 | 1 | 2 | 0 | 0.03 |
| 7645 | Margaret Mueller | 1 | 1 | 2 | 0 | 0.03 |
| 7646 | Margot Adam | 1 | 1 | 2 | 0 | 0.03 |
| 7647 | Marika Rörricht | 1 | 1 | 2 | 0 | 0.03 |
| 7648 | Marine Goncalves | 1 | 1 | 2 | 0 | 0.03 |
| 7649 | Martha Patrick | 1 | 1 | 2 | 0 | 0.03 |
| 7650 | Martin Anderson | 1 | 1 | 2 | 0 | 0.03 |
| 7651 | Martino Federico | 1 | 1 | 2 | 0 | 0.03 |
| 7652 | Mary Morales | 1 | 1 | 2 | 0 | 0.03 |
| 7653 | Mathilde Texier | 1 | 1 | 2 | 0 | 0.03 |
| 7654 | Matthew Davidson | 1 | 1 | 2 | 0 | 0.03 |
| 7655 | Matthew Phillips | 1 | 1 | 2 | 0 | 0.03 |
| 7656 | Maurycy Seidel | 1 | 1 | 2 | 0 | 0.03 |
| 7657 | Meghan Cortez | 1 | 1 | 2 | 0 | 0.03 |
| 7658 | Melanie Heß | 1 | 1 | 2 | 0 | 0.03 |
| 7659 | Michael Cole | 1 | 1 | 2 | 0 | 0.03 |
| 7660 | Michael Grant | 1 | 1 | 2 | 0 | 0.03 |
| 7661 | Michael Jackson | 1 | 1 | 2 | 0 | 0.03 |
| 7662 | Michael Roberts | 1 | 1 | 2 | 0 | 0.03 |
| 7663 | Michael Snyder | 1 | 1 | 2 | 0 | 0.03 |
| 7664 | Michael White | 1 | 1 | 2 | 0 | 0.03 |
| 7665 | Michaela Brooks | 1 | 1 | 2 | 0 | 0.03 |
| 7666 | Michelle Castro | 1 | 1 | 2 | 0 | 0.03 |
| 7667 | Michelle Gilbert | 1 | 1 | 2 | 0 | 0.03 |
| 7668 | Michelle Herrera | 1 | 1 | 2 | 0 | 0.03 |
| 7669 | Michelle Russo | 1 | 1 | 2 | 0 | 0.03 |
| 7670 | Michelle Shields | 1 | 1 | 2 | 0 | 0.03 |
| 7671 | Mikako Saito | 1 | 1 | 2 | 0 | 0.03 |
| 7672 | Min Du | 1 | 1 | 2 | 0 | 0.03 |
| 7673 | Min Kang | 1 | 1 | 2 | 0 | 0.03 |
| 7674 | Ming Meng | 1 | 1 | 2 | 0 | 0.03 |
| 7675 | Miss Erin Dean | 1 | 1 | 2 | 0 | 0.03 |
| 7676 | Mitchell Mcdonald | 1 | 1 | 2 | 0 | 0.03 |
| 7677 | Monica Coleman | 1 | 1 | 2 | 0 | 0.03 |
| 7678 | Monica Hunt | 1 | 1 | 2 | 0 | 0.03 |
| 7679 | Monica Mason | 1 | 1 | 2 | 0 | 0.03 |
| 7680 | Monika Leonowicz | 1 | 1 | 2 | 0 | 0.03 |
| 7681 | Na Huang | 1 | 1 | 2 | 0 | 0.03 |
| 7682 | Nancy Franklin | 1 | 1 | 2 | 0 | 0.03 |
| 7683 | Nancy Myers | 1 | 1 | 2 | 0 | 0.03 |
| 7684 | Naoko Suzuki | 1 | 1 | 2 | 0 | 0.03 |
| 7685 | Narrer på Vagt | 1 | 1 | 2 | 0 | 0.03 |
| 7686 | Natan Molka | 1 | 1 | 2 | 0 | 0.03 |
| 7687 | Navya Jhaveri | 1 | 1 | 2 | 0 | 0.03 |
| 7688 | Navya Kala | 1 | 1 | 2 | 0 | 0.03 |
| 7689 | Nicholas Rasmussen | 1 | 1 | 2 | 0 | 0.03 |
| 7690 | Nicolas Rodriguez | 1 | 1 | 2 | 0 | 0.03 |
| 7691 | Nicole Valenzuela | 1 | 1 | 2 | 0 | 0.03 |
| 7692 | Nino Pometta | 1 | 1 | 2 | 0 | 0.03 |
| 7693 | Olivia Jarvis | 1 | 1 | 2 | 0 | 0.03 |
| 7694 | Onofre Chacón Jordá | 1 | 1 | 2 | 0 | 0.03 |
| 7695 | Ottilie Fiebig | 1 | 1 | 2 | 0 | 0.03 |
| 7696 | Paco Yáñez Bravo | 1 | 1 | 2 | 0 | 0.03 |
| 7697 | Parinaaz Krishnamurthy | 1 | 1 | 2 | 0 | 0.03 |
| 7698 | Patricia Cherry | 1 | 1 | 2 | 0 | 0.03 |
| 7699 | Patrick Herrera | 1 | 1 | 2 | 0 | 0.03 |
| 7700 | Patrizia Drewes | 1 | 1 | 2 | 0 | 0.03 |
| 7701 | Paul Kirk | 1 | 1 | 2 | 0 | 0.03 |
| 7702 | Philippine du Pottier | 1 | 1 | 2 | 0 | 0.03 |
| 7703 | Pierre David | 1 | 1 | 2 | 0 | 0.03 |
| 7704 | Ping Fang | 1 | 1 | 2 | 0 | 0.03 |
| 7705 | Rafał Helak | 1 | 1 | 2 | 0 | 0.03 |
| 7706 | Raymond Blackburn | 1 | 1 | 2 | 0 | 0.03 |
| 7707 | Raymond Gates | 1 | 1 | 2 | 0 | 0.03 |
| 7708 | Raymond Martin | 1 | 1 | 2 | 0 | 0.03 |
| 7709 | Rebecca Bishop | 1 | 1 | 2 | 0 | 0.03 |
| 7710 | Rebecca Byrd | 1 | 1 | 2 | 0 | 0.03 |
| 7711 | Recep Schüler | 1 | 1 | 2 | 0 | 0.03 |
| 7712 | Regina Vance | 1 | 1 | 2 | 0 | 0.03 |
| 7713 | Renee Carr | 1 | 1 | 2 | 0 | 0.03 |
| 7714 | Reyansh Barad | 1 | 1 | 2 | 0 | 0.03 |
| 7715 | Rhea Chatterjee | 1 | 1 | 2 | 0 | 0.03 |
| 7716 | Rhea Dhar | 1 | 1 | 2 | 0 | 0.03 |
| 7717 | Rhonda Guerrero | 1 | 1 | 2 | 0 | 0.03 |
| 7718 | Richard Kaiser | 1 | 1 | 2 | 0 | 0.03 |
| 7719 | Richard Mckenzie | 1 | 1 | 2 | 0 | 0.03 |
| 7720 | Richard Vazquez | 1 | 1 | 2 | 0 | 0.03 |
| 7721 | Richard Ward | 1 | 1 | 2 | 0 | 0.03 |
| 7722 | Ritvik Venkatesh | 1 | 1 | 2 | 0 | 0.03 |
| 7723 | Robert Fernandez | 1 | 1 | 2 | 0 | 0.03 |
| 7724 | Robert Fowler | 1 | 1 | 2 | 0 | 0.03 |
| 7725 | Robert Gonzales | 1 | 1 | 2 | 0 | 0.03 |
| 7726 | Robert Nelson | 1 | 1 | 2 | 0 | 0.03 |
| 7727 | Robert Renault | 1 | 1 | 2 | 0 | 0.03 |
| 7728 | Rodney Hayes | 1 | 1 | 2 | 0 | 0.03 |
| 7729 | Roksana Kurzak | 1 | 1 | 2 | 0 | 0.03 |
| 7730 | Rolando Paruta | 1 | 1 | 2 | 0 | 0.03 |
| 7731 | Ronald Esparza | 1 | 1 | 2 | 0 | 0.03 |
| 7732 | Rosa-Maria Beyer | 1 | 1 | 2 | 0 | 0.03 |
| 7733 | Rosenda Reyes Salazar | 1 | 1 | 2 | 0 | 0.03 |
| 7734 | Ryan Hamilton | 1 | 1 | 2 | 0 | 0.03 |
| 7735 | Ryan Richards | 1 | 1 | 2 | 0 | 0.03 |
| 7736 | Ryan Smith | 1 | 1 | 2 | 0 | 0.03 |
| 7737 | Ryohei Nakajima | 1 | 1 | 2 | 0 | 0.03 |
| 7738 | Ryosuke Nakamura | 1 | 1 | 2 | 0 | 0.03 |
| 7739 | Rüdiger Schinke | 1 | 1 | 2 | 0 | 0.03 |
| 7740 | Saira Bose | 1 | 1 | 2 | 0 | 0.03 |
| 7741 | Samantha Taylor | 1 | 1 | 2 | 0 | 0.03 |
| 7742 | Samiha Hayre | 1 | 1 | 2 | 0 | 0.03 |
| 7743 | Samuel Lewis | 1 | 1 | 2 | 0 | 0.03 |
| 7744 | Sandra Riley | 1 | 1 | 2 | 0 | 0.03 |
| 7745 | Sara Seguí Vallés | 1 | 1 | 2 | 0 | 0.03 |
| 7746 | Sara Sharaf | 1 | 1 | 2 | 0 | 0.03 |
| 7747 | Scott Gutierrez | 1 | 1 | 2 | 0 | 0.03 |
| 7748 | Shane Clark | 1 | 1 | 2 | 0 | 0.03 |
| 7749 | Shannon Castro | 1 | 1 | 2 | 0 | 0.03 |
| 7750 | Sharon Roberts | 1 | 1 | 2 | 0 | 0.03 |
| 7751 | Shawn Hart | 1 | 1 | 2 | 0 | 0.03 |
| 7752 | Shohei Yamashita | 1 | 1 | 2 | 0 | 0.03 |
| 7753 | Shota Mori | 1 | 1 | 2 | 0 | 0.03 |
| 7754 | Stephanie Benjamin | 1 | 1 | 2 | 0 | 0.03 |
| 7755 | Stephanie Brown | 1 | 1 | 2 | 0 | 0.03 |
| 7756 | Stephanie Hanson | 1 | 1 | 2 | 0 | 0.03 |
| 7757 | Stephen Chavez | 1 | 1 | 2 | 0 | 0.03 |
| 7758 | Steve Schottin | 1 | 1 | 2 | 0 | 0.03 |
| 7759 | Steven Williams | 1 | 1 | 2 | 0 | 0.03 |
| 7760 | Summer Bender | 1 | 1 | 2 | 0 | 0.03 |
| 7761 | Suzanne Ramos | 1 | 1 | 2 | 0 | 0.03 |
| 7762 | Sven Oude Heer | 1 | 1 | 2 | 0 | 0.03 |
| 7763 | Takuma Shimizu | 1 | 1 | 2 | 0 | 0.03 |
| 7764 | Tammy Crane | 1 | 1 | 2 | 0 | 0.03 |
| 7765 | Tao Fan | 1 | 1 | 2 | 0 | 0.03 |
| 7766 | Tara Becker | 1 | 1 | 2 | 0 | 0.03 |
| 7767 | Tara Kaul | 1 | 1 | 2 | 0 | 0.03 |
| 7768 | Taylor Poole | 1 | 1 | 2 | 0 | 0.03 |
| 7769 | Terry Baker | 1 | 1 | 2 | 0 | 0.03 |
| 7770 | Theres Roht | 1 | 1 | 2 | 0 | 0.03 |
| 7771 | Thomas Boyle | 1 | 1 | 2 | 0 | 0.03 |
| 7772 | Thomas Duncan | 1 | 1 | 2 | 0 | 0.03 |
| 7773 | Thomas Mccoy | 1 | 1 | 2 | 0 | 0.03 |
| 7774 | Thomas Ramirez | 1 | 1 | 2 | 0 | 0.03 |
| 7775 | Tiffany Wong | 1 | 1 | 2 | 0 | 0.03 |
| 7776 | Timothy Chen | 1 | 1 | 2 | 0 | 0.03 |
| 7777 | Timothy Haley | 1 | 1 | 2 | 0 | 0.03 |
| 7778 | Timothy Kelly | 1 | 1 | 2 | 0 | 0.03 |
| 7779 | Timothée Lefèvre | 1 | 1 | 2 | 0 | 0.03 |
| 7780 | Tobiasz Kargol | 1 | 1 | 2 | 0 | 0.03 |
| 7781 | Tom Kade | 1 | 1 | 2 | 0 | 0.03 |
| 7782 | Tracy Combs | 1 | 1 | 2 | 0 | 0.03 |
| 7783 | Tracy Vazquez | 1 | 1 | 2 | 0 | 0.03 |
| 7784 | Traude Salz | 1 | 1 | 2 | 0 | 0.03 |
| 7785 | Traudl Jacob | 1 | 1 | 2 | 0 | 0.03 |
| 7786 | Travis Schmitt | 1 | 1 | 2 | 0 | 0.03 |
| 7787 | Trevor Gonzales | 1 | 1 | 2 | 0 | 0.03 |
| 7788 | Tyler Smith | 1 | 1 | 2 | 0 | 0.03 |
| 7789 | Tülay Tlustek | 1 | 1 | 2 | 0 | 0.03 |
| 7790 | Valentine Jourdan du Schneider | 1 | 1 | 2 | 0 | 0.03 |
| 7791 | Valerio Zapata-Rico | 1 | 1 | 2 | 0 | 0.03 |
| 7792 | Vedika Dar | 1 | 1 | 2 | 0 | 0.03 |
| 7793 | Veer Raju | 1 | 1 | 2 | 0 | 0.03 |
| 7794 | Vidur Khatri | 1 | 1 | 2 | 0 | 0.03 |
| 7795 | William Bates | 1 | 1 | 2 | 0 | 0.03 |
| 7796 | William Kennedy | 1 | 1 | 2 | 0 | 0.03 |
| 7797 | William Warren | 1 | 1 | 2 | 0 | 0.03 |
| 7798 | Wojciech Ratka | 1 | 1 | 2 | 0 | 0.03 |
| 7799 | Xia Tao | 1 | 1 | 2 | 0 | 0.03 |
| 7800 | Xia Yan | 1 | 1 | 2 | 0 | 0.03 |
| 7801 | Xiulan Chen | 1 | 1 | 2 | 0 | 0.03 |
| 7802 | Xiuying Yi | 1 | 1 | 2 | 0 | 0.03 |
| 7803 | Yan Mo | 1 | 1 | 2 | 0 | 0.03 |
| 7804 | Yang Fu | 1 | 1 | 2 | 0 | 0.03 |
| 7805 | Yang Shi | 1 | 1 | 2 | 0 | 0.03 |
| 7806 | Yolanda Mendoza | 1 | 1 | 2 | 0 | 0.03 |
| 7807 | Yolanda Roy | 1 | 1 | 2 | 0 | 0.03 |
| 7808 | Yong Zhao | 1 | 1 | 2 | 0 | 0.03 |
| 7809 | Zain Datta | 1 | 1 | 2 | 0 | 0.03 |
| 7810 | Élise Moreno | 1 | 1 | 2 | 0 | 0.03 |
| 7811 | Anthony Clark | 1 | 0 | 15 | 1 | 0.03 |
| 7812 | Deborah Matthews | 1 | 0 | 15 | 1 | 0.03 |
| 7813 | Douglas Haynes | 1 | 0 | 15 | 1 | 0.03 |
| 7814 | Jochen Becker | 1 | 0 | 15 | 1 | 0.03 |
| 7815 | John Mitchell | 1 | 0 | 15 | 1 | 0.03 |
| 7816 | Rhonda Ward | 1 | 0 | 15 | 1 | 0.03 |
| 7817 | Stilla Seifert | 1 | 0 | 15 | 1 | 0.03 |
| 7818 | Tilly Eigenwillig | 1 | 0 | 15 | 1 | 0.03 |
| 7819 | Timothy Simpson | 1 | 0 | 15 | 1 | 0.03 |
| 7820 | Aaron Jones | 1 | 1 | 1 | 0 | 0.03 |
| 7821 | Abraham Becker | 1 | 1 | 1 | 0 | 0.03 |
| 7822 | Agnes Stahr | 1 | 1 | 1 | 0 | 0.03 |
| 7823 | Ahana Sarin | 1 | 1 | 1 | 0 | 0.03 |
| 7824 | Akemi Nishimura | 1 | 1 | 1 | 0 | 0.03 |
| 7825 | Akemi Suzuki | 1 | 1 | 1 | 0 | 0.03 |
| 7826 | Alan Castro | 1 | 1 | 1 | 0 | 0.03 |
| 7827 | Alan Smith | 1 | 1 | 1 | 0 | 0.03 |
| 7828 | Alan Yang | 1 | 1 | 1 | 0 | 0.03 |
| 7829 | Albert White | 1 | 1 | 1 | 0 | 0.03 |
| 7830 | Albrecht Scholtz | 1 | 1 | 1 | 0 | 0.03 |
| 7831 | Alejandro Brown | 1 | 1 | 1 | 0 | 0.03 |
| 7832 | Alexis Church | 1 | 1 | 1 | 0 | 0.03 |
| 7833 | Alphonse Berthelot | 1 | 1 | 1 | 0 | 0.03 |
| 7834 | Amanda Mcdonald | 1 | 1 | 1 | 0 | 0.03 |
| 7835 | Amelie Roht | 1 | 1 | 1 | 0 | 0.03 |
| 7836 | Ana Garrison | 1 | 1 | 1 | 0 | 0.03 |
| 7837 | Ana Wilson | 1 | 1 | 1 | 0 | 0.03 |
| 7838 | Andrea Ramirez | 1 | 1 | 1 | 0 | 0.03 |
| 7839 | Angelica Ruiz | 1 | 1 | 1 | 0 | 0.03 |
| 7840 | Anthony Larson | 1 | 1 | 1 | 0 | 0.03 |
| 7841 | Autumn Knight | 1 | 1 | 1 | 0 | 0.03 |
| 7842 | Baccio Caracciolo-Pelli | 1 | 1 | 1 | 0 | 0.03 |
| 7843 | Beata Budig | 1 | 1 | 1 | 0 | 0.03 |
| 7844 | Bianca Pugliese | 1 | 1 | 1 | 0 | 0.03 |
| 7845 | Brandon Waller | 1 | 1 | 1 | 0 | 0.03 |
| 7846 | Carlos Franco | 1 | 1 | 1 | 0 | 0.03 |
| 7847 | Carrie Morris | 1 | 1 | 1 | 0 | 0.03 |
| 7848 | Catherine Parker | 1 | 1 | 1 | 0 | 0.03 |
| 7849 | Charles Normand | 1 | 1 | 1 | 0 | 0.03 |
| 7850 | Charles Shaw | 1 | 1 | 1 | 0 | 0.03 |
| 7851 | Chelsea Mata | 1 | 1 | 1 | 0 | 0.03 |
| 7852 | Chiyo Nakajima | 1 | 1 | 1 | 0 | 0.03 |
| 7853 | Christopher Brown | 1 | 1 | 1 | 0 | 0.03 |
| 7854 | Christopher Wells | 1 | 1 | 1 | 0 | 0.03 |
| 7855 | Christy Hicks | 1 | 1 | 1 | 0 | 0.03 |
| 7856 | Concha Roselló Verdugo | 1 | 1 | 1 | 0 | 0.03 |
| 7857 | Cynthia Johnson | 1 | 1 | 1 | 0 | 0.03 |
| 7858 | Cynthia Pierce | 1 | 1 | 1 | 0 | 0.03 |
| 7859 | Cyprian Goss | 1 | 1 | 1 | 0 | 0.03 |
| 7860 | DRIP$ETTA | 1 | 1 | 1 | 0 | 0.03 |
| 7861 | Darshit Gandhi | 1 | 1 | 1 | 0 | 0.03 |
| 7862 | Darshit Ratta | 1 | 1 | 1 | 0 | 0.03 |
| 7863 | David Campbell | 1 | 1 | 1 | 0 | 0.03 |
| 7864 | Deborah Cruz | 1 | 1 | 1 | 0 | 0.03 |
| 7865 | Deborah Young | 1 | 1 | 1 | 0 | 0.03 |
| 7866 | Debra Jones | 1 | 1 | 1 | 0 | 0.03 |
| 7867 | Devansh De | 1 | 1 | 1 | 0 | 0.03 |
| 7868 | Dhanuk Mane | 1 | 1 | 1 | 0 | 0.03 |
| 7869 | Diana Wilkinson | 1 | 1 | 1 | 0 | 0.03 |
| 7870 | Divyansh Sehgal | 1 | 1 | 1 | 0 | 0.03 |
| 7871 | Dustin Maxwell | 1 | 1 | 1 | 0 | 0.03 |
| 7872 | Elizabeth Montgomery | 1 | 1 | 1 | 0 | 0.03 |
| 7873 | Emily Hudson | 1 | 1 | 1 | 0 | 0.03 |
| 7874 | Enzio Caffarelli | 1 | 1 | 1 | 0 | 0.03 |
| 7875 | Erin Martinez | 1 | 1 | 1 | 0 | 0.03 |
| 7876 | Ethan Wiley | 1 | 1 | 1 | 0 | 0.03 |
| 7877 | Eulalia Patiño Ballester | 1 | 1 | 1 | 0 | 0.03 |
| 7878 | Evie Feenstra | 1 | 1 | 1 | 0 | 0.03 |
| 7879 | Fateh Bhatt | 1 | 1 | 1 | 0 | 0.03 |
| 7880 | Folkert Schmidtke | 1 | 1 | 1 | 0 | 0.03 |
| 7881 | Francisco Säuberlich | 1 | 1 | 1 | 0 | 0.03 |
| 7882 | Franck du Mercier | 1 | 1 | 1 | 0 | 0.03 |
| 7883 | Gabrielle Brady | 1 | 1 | 1 | 0 | 0.03 |
| 7884 | Gaja Powierża | 1 | 1 | 1 | 0 | 0.03 |
| 7885 | Gary Wilson | 1 | 1 | 1 | 0 | 0.03 |
| 7886 | George Bailey | 1 | 1 | 1 | 0 | 0.03 |
| 7887 | Gianmarco Verga | 1 | 1 | 1 | 0 | 0.03 |
| 7888 | Giovanna Bongiorno | 1 | 1 | 1 | 0 | 0.03 |
| 7889 | Giulietta Parini | 1 | 1 | 1 | 0 | 0.03 |
| 7890 | Grant Bruce | 1 | 1 | 1 | 0 | 0.03 |
| 7891 | Gregory Evans | 1 | 1 | 1 | 0 | 0.03 |
| 7892 | Guiying Mao | 1 | 1 | 1 | 0 | 0.03 |
| 7893 | Hannah Richard | 1 | 1 | 1 | 0 | 0.03 |
| 7894 | Hans-Joachim Seip | 1 | 1 | 1 | 0 | 0.03 |
| 7895 | Heather Davis | 1 | 1 | 1 | 0 | 0.03 |
| 7896 | Heinz-Georg Bolzmann | 1 | 1 | 1 | 0 | 0.03 |
| 7897 | Hilma Wirth | 1 | 1 | 1 | 0 | 0.03 |
| 7898 | Hortense Peron | 1 | 1 | 1 | 0 | 0.03 |
| 7899 | Hrishita Deep | 1 | 1 | 1 | 0 | 0.03 |
| 7900 | Hunar Dugal | 1 | 1 | 1 | 0 | 0.03 |
| 7901 | Imke Hartmann | 1 | 1 | 1 | 0 | 0.03 |
| 7902 | Indrajit Chana | 1 | 1 | 1 | 0 | 0.03 |
| 7903 | Ira Gole | 1 | 1 | 1 | 0 | 0.03 |
| 7904 | Ishaan Bal | 1 | 1 | 1 | 0 | 0.03 |
| 7905 | Isla Quinn | 1 | 1 | 1 | 0 | 0.03 |
| 7906 | Ivana Dhillon | 1 | 1 | 1 | 0 | 0.03 |
| 7907 | Jacek Kazimierczuk | 1 | 1 | 1 | 0 | 0.03 |
| 7908 | Jacob Bryant | 1 | 1 | 1 | 0 | 0.03 |
| 7909 | Jacob Gallagher | 1 | 1 | 1 | 0 | 0.03 |
| 7910 | James Gibbs | 1 | 1 | 1 | 0 | 0.03 |
| 7911 | James Harvey | 1 | 1 | 1 | 0 | 0.03 |
| 7912 | Janet Powers | 1 | 1 | 1 | 0 | 0.03 |
| 7913 | Janette Reuter | 1 | 1 | 1 | 0 | 0.03 |
| 7914 | Janice Villarreal | 1 | 1 | 1 | 0 | 0.03 |
| 7915 | Janna Holt | 1 | 1 | 1 | 0 | 0.03 |
| 7916 | Jason Mcpherson | 1 | 1 | 1 | 0 | 0.03 |
| 7917 | Jason Owens | 1 | 1 | 1 | 0 | 0.03 |
| 7918 | Jayan Barman | 1 | 1 | 1 | 0 | 0.03 |
| 7919 | Jeff Lewis | 1 | 1 | 1 | 0 | 0.03 |
| 7920 | Jeffrey Garrett | 1 | 1 | 1 | 0 | 0.03 |
| 7921 | Jeffrey Morgan | 1 | 1 | 1 | 0 | 0.03 |
| 7922 | Jenna Casey | 1 | 1 | 1 | 0 | 0.03 |
| 7923 | Jennifer Coleman | 1 | 1 | 1 | 0 | 0.03 |
| 7924 | Jennifer Ferguson | 1 | 1 | 1 | 0 | 0.03 |
| 7925 | Jessica Carney | 1 | 1 | 1 | 0 | 0.03 |
| 7926 | Jessica Garcia | 1 | 1 | 1 | 0 | 0.03 |
| 7927 | Jie Guo | 1 | 1 | 1 | 0 | 0.03 |
| 7928 | Jimmy Brown | 1 | 1 | 1 | 0 | 0.03 |
| 7929 | Jivin Wali | 1 | 1 | 1 | 0 | 0.03 |
| 7930 | Jodi Salazar | 1 | 1 | 1 | 0 | 0.03 |
| 7931 | Joe Mccarthy | 1 | 1 | 1 | 0 | 0.03 |
| 7932 | Jonathan Bishop | 1 | 1 | 1 | 0 | 0.03 |
| 7933 | Jonathan Thompson | 1 | 1 | 1 | 0 | 0.03 |
| 7934 | Jorge Atkinson | 1 | 1 | 1 | 0 | 0.03 |
| 7935 | Josep Nicanor Salcedo Arroyo | 1 | 1 | 1 | 0 | 0.03 |
| 7936 | Joseph Adams | 1 | 1 | 1 | 0 | 0.03 |
| 7937 | Joseph Contreras | 1 | 1 | 1 | 0 | 0.03 |
| 7938 | Joseph Wright | 1 | 1 | 1 | 0 | 0.03 |
| 7939 | Joshua Morrison | 1 | 1 | 1 | 0 | 0.03 |
| 7940 | Juan Qin | 1 | 1 | 1 | 0 | 0.03 |
| 7941 | Juan Yi | 1 | 1 | 1 | 0 | 0.03 |
| 7942 | Julianna Mytnik | 1 | 1 | 1 | 0 | 0.03 |
| 7943 | Julie Flores | 1 | 1 | 1 | 0 | 0.03 |
| 7944 | Julita Łaciak | 1 | 1 | 1 | 0 | 0.03 |
| 7945 | Juliusz Cierpisz | 1 | 1 | 1 | 0 | 0.03 |
| 7946 | Juliusz Hawrylak | 1 | 1 | 1 | 0 | 0.03 |
| 7947 | Kabir Dutta | 1 | 1 | 1 | 0 | 0.03 |
| 7948 | Karol Szczechowicz | 1 | 1 | 1 | 0 | 0.03 |
| 7949 | Kelly Briggs | 1 | 1 | 1 | 0 | 0.03 |
| 7950 | Kenichi Suzuki | 1 | 1 | 1 | 0 | 0.03 |
| 7951 | Kenneth Guerra | 1 | 1 | 1 | 0 | 0.03 |
| 7952 | Kenneth Ruiz | 1 | 1 | 1 | 0 | 0.03 |
| 7953 | Kevin Ayala | 1 | 1 | 1 | 0 | 0.03 |
| 7954 | Kevin Gilbert | 1 | 1 | 1 | 0 | 0.03 |
| 7955 | Kim Craig | 1 | 1 | 1 | 0 | 0.03 |
| 7956 | Kimaya Chaudhuri | 1 | 1 | 1 | 0 | 0.03 |
| 7957 | Kimberly Jones | 1 | 1 | 1 | 0 | 0.03 |
| 7958 | Kumiko Sato | 1 | 1 | 1 | 0 | 0.03 |
| 7959 | Kyle Cook | 1 | 1 | 1 | 0 | 0.03 |
| 7960 | Kyle Jackson | 1 | 1 | 1 | 0 | 0.03 |
| 7961 | Leroy Reeves | 1 | 1 | 1 | 0 | 0.03 |
| 7962 | Li Wang | 1 | 1 | 1 | 0 | 0.03 |
| 7963 | Lina Rensi | 1 | 1 | 1 | 0 | 0.03 |
| 7964 | Lisa Johnson | 1 | 1 | 1 | 0 | 0.03 |
| 7965 | Lori Schmidt | 1 | 1 | 1 | 0 | 0.03 |
| 7966 | Luc van Poppel-Hulskes | 1 | 1 | 1 | 0 | 0.03 |
| 7967 | Lucas Lenoir du Colin | 1 | 1 | 1 | 0 | 0.03 |
| 7968 | Maks Bodek | 1 | 1 | 1 | 0 | 0.03 |
| 7969 | Maks Grębowiec | 1 | 1 | 1 | 0 | 0.03 |
| 7970 | Marcin Jeżyk | 1 | 1 | 1 | 0 | 0.03 |
| 7971 | Marion Hellwig-Berger | 1 | 1 | 1 | 0 | 0.03 |
| 7972 | Mark Singleton | 1 | 1 | 1 | 0 | 0.03 |
| 7973 | Mary Frazier | 1 | 1 | 1 | 0 | 0.03 |
| 7974 | Mary Gordon | 1 | 1 | 1 | 0 | 0.03 |
| 7975 | Mary Mies | 1 | 1 | 1 | 0 | 0.03 |
| 7976 | Mary Williams | 1 | 1 | 1 | 0 | 0.03 |
| 7977 | Matthew Tran | 1 | 1 | 1 | 0 | 0.03 |
| 7978 | Max Brown | 1 | 1 | 1 | 0 | 0.03 |
| 7979 | Mckenzie Cuevas | 1 | 1 | 1 | 0 | 0.03 |
| 7980 | Mehul Varty | 1 | 1 | 1 | 0 | 0.03 |
| 7981 | Melanie Browning PhD | 1 | 1 | 1 | 0 | 0.03 |
| 7982 | Melissa Watson | 1 | 1 | 1 | 0 | 0.03 |
| 7983 | Michael Farrell | 1 | 1 | 1 | 0 | 0.03 |
| 7984 | Michael Lin | 1 | 1 | 1 | 0 | 0.03 |
| 7985 | Michelle Montoya | 1 | 1 | 1 | 0 | 0.03 |
| 7986 | Miluše Malá | 1 | 1 | 1 | 0 | 0.03 |
| 7987 | Min Xiao | 1 | 1 | 1 | 0 | 0.03 |
| 7988 | Na Ding | 1 | 1 | 1 | 0 | 0.03 |
| 7989 | Na Tao | 1 | 1 | 1 | 0 | 0.03 |
| 7990 | Natasha Wood | 1 | 1 | 1 | 0 | 0.03 |
| 7991 | Nathan Hernandez | 1 | 1 | 1 | 0 | 0.03 |
| 7992 | Nathaniel Fisher | 1 | 1 | 1 | 0 | 0.03 |
| 7993 | Nicholas Pope | 1 | 1 | 1 | 0 | 0.03 |
| 7994 | Nicolai Caspar | 1 | 1 | 1 | 0 | 0.03 |
| 7995 | Nino Canova-Esposito | 1 | 1 | 1 | 0 | 0.03 |
| 7996 | Ottomar Spieß | 1 | 1 | 1 | 0 | 0.03 |
| 7997 | Pamela Moran | 1 | 1 | 1 | 0 | 0.03 |
| 7998 | Pamela Schultz | 1 | 1 | 1 | 0 | 0.03 |
| 7999 | Pari Sharaf | 1 | 1 | 1 | 0 | 0.03 |
| 8000 | Paul Ashley | 1 | 1 | 1 | 0 | 0.03 |
| 8001 | Paul Contreras | 1 | 1 | 1 | 0 | 0.03 |
| 8002 | Phillip Dennis | 1 | 1 | 1 | 0 | 0.03 |
| 8003 | Ping Zhao | 1 | 1 | 1 | 0 | 0.03 |
| 8004 | Piya Ravel | 1 | 1 | 1 | 0 | 0.03 |
| 8005 | Qiang Hou | 1 | 1 | 1 | 0 | 0.03 |
| 8006 | Rachel Lewis | 1 | 1 | 1 | 0 | 0.03 |
| 8007 | Richard Mathieu de Perrin | 1 | 1 | 1 | 0 | 0.03 |
| 8008 | Ritvik Taneja | 1 | 1 | 1 | 0 | 0.03 |
| 8009 | Riya Dhingra | 1 | 1 | 1 | 0 | 0.03 |
| 8010 | Robert Bass | 1 | 1 | 1 | 0 | 0.03 |
| 8011 | Robert Strickland | 1 | 1 | 1 | 0 | 0.03 |
| 8012 | Ronald Barnett | 1 | 1 | 1 | 0 | 0.03 |
| 8013 | Rosa Flaiano | 1 | 1 | 1 | 0 | 0.03 |
| 8014 | Ruben Green | 1 | 1 | 1 | 0 | 0.03 |
| 8015 | Ryan Howard | 1 | 1 | 1 | 0 | 0.03 |
| 8016 | Ryan King | 1 | 1 | 1 | 0 | 0.03 |
| 8017 | Ryan Murphy | 1 | 1 | 1 | 0 | 0.03 |
| 8018 | Sabrina Hughes | 1 | 1 | 1 | 0 | 0.03 |
| 8019 | Samaira Borah | 1 | 1 | 1 | 0 | 0.03 |
| 8020 | Samarth Saraf | 1 | 1 | 1 | 0 | 0.03 |
| 8021 | Sandra Horton | 1 | 1 | 1 | 0 | 0.03 |
| 8022 | Sandra Reyes | 1 | 1 | 1 | 0 | 0.03 |
| 8023 | Sara Levy | 1 | 1 | 1 | 0 | 0.03 |
| 8024 | Sarah Anderson | 1 | 1 | 1 | 0 | 0.03 |
| 8025 | Scott Kemp | 1 | 1 | 1 | 0 | 0.03 |
| 8026 | Shannon Schaefer | 1 | 1 | 1 | 0 | 0.03 |
| 8027 | Shawn Saunders | 1 | 1 | 1 | 0 | 0.03 |
| 8028 | Shelia Miller | 1 | 1 | 1 | 0 | 0.03 |
| 8029 | Shlok Cherian | 1 | 1 | 1 | 0 | 0.03 |
| 8030 | Shota Ito | 1 | 1 | 1 | 0 | 0.03 |
| 8031 | Simone Maurice | 1 | 1 | 1 | 0 | 0.03 |
| 8032 | Stacey Perry | 1 | 1 | 1 | 0 | 0.03 |
| 8033 | Stacy Davenport | 1 | 1 | 1 | 0 | 0.03 |
| 8034 | Stephanie Potter | 1 | 1 | 1 | 0 | 0.03 |
| 8035 | Susan Romero | 1 | 1 | 1 | 0 | 0.03 |
| 8036 | Sylwia Hołota | 1 | 1 | 1 | 0 | 0.03 |
| 8037 | Tanya Garrett | 1 | 1 | 1 | 0 | 0.03 |
| 8038 | Tara Dennis | 1 | 1 | 1 | 0 | 0.03 |
| 8039 | Tara Deshmukh | 1 | 1 | 1 | 0 | 0.03 |
| 8040 | Tara Ghose | 1 | 1 | 1 | 0 | 0.03 |
| 8041 | Tara Rivera | 1 | 1 | 1 | 0 | 0.03 |
| 8042 | Teófilo Flor Gras | 1 | 1 | 1 | 0 | 0.03 |
| 8043 | The Lunar Manifesto | 1 | 1 | 1 | 0 | 0.03 |
| 8044 | Thomas Carson | 1 | 1 | 1 | 0 | 0.03 |
| 8045 | Thomas Jones | 1 | 1 | 1 | 0 | 0.03 |
| 8046 | Tiffany Fitzpatrick | 1 | 1 | 1 | 0 | 0.03 |
| 8047 | Tiya Desai | 1 | 1 | 1 | 0 | 0.03 |
| 8048 | Tricia Yoder | 1 | 1 | 1 | 0 | 0.03 |
| 8049 | Tsubasa Sasaki | 1 | 1 | 1 | 0 | 0.03 |
| 8050 | Umang Bala | 1 | 1 | 1 | 0 | 0.03 |
| 8051 | Valentina Geraci | 1 | 1 | 1 | 0 | 0.03 |
| 8052 | Vincent Berg | 1 | 1 | 1 | 0 | 0.03 |
| 8053 | Vivaan Kala | 1 | 1 | 1 | 0 | 0.03 |
| 8054 | Vlastimil Bílek | 1 | 1 | 1 | 0 | 0.03 |
| 8055 | Wei Jiang | 1 | 1 | 1 | 0 | 0.03 |
| 8056 | William Fritz | 1 | 1 | 1 | 0 | 0.03 |
| 8057 | William Garner | 1 | 1 | 1 | 0 | 0.03 |
| 8058 | William Navarro | 1 | 1 | 1 | 0 | 0.03 |
| 8059 | William Ruiz | 1 | 1 | 1 | 0 | 0.03 |
| 8060 | William Tran | 1 | 1 | 1 | 0 | 0.03 |
| 8061 | Xia Huang | 1 | 1 | 1 | 0 | 0.03 |
| 8062 | Xiulan Xiao | 1 | 1 | 1 | 0 | 0.03 |
| 8063 | Yan Zeng | 1 | 1 | 1 | 0 | 0.03 |
| 8064 | Yan Zhang | 1 | 1 | 1 | 0 | 0.03 |
| 8065 | Yang Gong | 1 | 1 | 1 | 0 | 0.03 |
| 8066 | Yasmin Vig | 1 | 1 | 1 | 0 | 0.03 |
| 8067 | Yasuhiro Nakamura | 1 | 1 | 1 | 0 | 0.03 |
| 8068 | Yong Wan | 1 | 1 | 1 | 0 | 0.03 |
| 8069 | Emmanuelle Leleu | 1 | 0 | 14 | 1 | 0.03 |
| 8070 | Gilles Peltier-Rocher | 1 | 0 | 14 | 1 | 0.03 |
| 8071 | Adrian Bridges | 1 | 0 | 10 | 2 | 0.03 |
| 8072 | Annalisa Saragat-Pininfarina | 1 | 0 | 10 | 2 | 0.03 |
| 8073 | Christian Scott | 1 | 0 | 10 | 2 | 0.03 |
| 8074 | Lolita Speri | 1 | 0 | 10 | 2 | 0.03 |
| 8075 | Margaret Brun | 1 | 0 | 10 | 2 | 0.03 |
| 8076 | Vanessa Leon | 1 | 0 | 10 | 2 | 0.03 |
| 8077 | Alex Steele | 1 | 1 | 0 | 0 | 0.03 |
| 8078 | Amanda Powell | 1 | 1 | 0 | 0 | 0.03 |
| 8079 | Andrea Green | 1 | 1 | 0 | 0 | 0.03 |
| 8080 | Anna Reyes | 1 | 1 | 0 | 0 | 0.03 |
| 8081 | Caroline Lloyd | 1 | 1 | 0 | 0 | 0.03 |
| 8082 | Christopher Glover | 1 | 1 | 0 | 0 | 0.03 |
| 8083 | Christopher Ward | 1 | 1 | 0 | 0 | 0.03 |
| 8084 | Filippa Piane | 1 | 1 | 0 | 0 | 0.03 |
| 8085 | Frederik Hartung | 1 | 1 | 0 | 0 | 0.03 |
| 8086 | Heidi Berry | 1 | 1 | 0 | 0 | 0.03 |
| 8087 | Hridaan Rout | 1 | 1 | 0 | 0 | 0.03 |
| 8088 | James Goodwin | 1 | 1 | 0 | 0 | 0.03 |
| 8089 | Jeffery Reese | 1 | 1 | 0 | 0 | 0.03 |
| 8090 | Jeffrey Middleton | 1 | 1 | 0 | 0 | 0.03 |
| 8091 | Jessica Russell | 1 | 1 | 0 | 0 | 0.03 |
| 8092 | Joan Taylor | 1 | 1 | 0 | 0 | 0.03 |
| 8093 | John Baxter | 1 | 1 | 0 | 0 | 0.03 |
| 8094 | Julie Larson | 1 | 1 | 0 | 0 | 0.03 |
| 8095 | Katherine Davis | 1 | 1 | 0 | 0 | 0.03 |
| 8096 | Katherine Stevens | 1 | 1 | 0 | 0 | 0.03 |
| 8097 | Klara Bisaga | 1 | 1 | 0 | 0 | 0.03 |
| 8098 | Konrad Koźlak | 1 | 1 | 0 | 0 | 0.03 |
| 8099 | Laura Cohen | 1 | 1 | 0 | 0 | 0.03 |
| 8100 | Lisa Maxwell | 1 | 1 | 0 | 0 | 0.03 |
| 8101 | Marit Thies | 1 | 1 | 0 | 0 | 0.03 |
| 8102 | Matthew Sanchez | 1 | 1 | 0 | 0 | 0.03 |
| 8103 | Michał Flasza | 1 | 1 | 0 | 0 | 0.03 |
| 8104 | Nanami Sakamoto | 1 | 1 | 0 | 0 | 0.03 |
| 8105 | Nicholas Johnson | 1 | 1 | 0 | 0 | 0.03 |
| 8106 | Radosław Krzyk | 1 | 1 | 0 | 0 | 0.03 |
| 8107 | Susan Jones | 1 | 1 | 0 | 0 | 0.03 |
| 8108 | Svetlana Freudenberger | 1 | 1 | 0 | 0 | 0.03 |
| 8109 | Tadeusz Kieszek | 1 | 1 | 0 | 0 | 0.03 |
| 8110 | Terry Olson | 1 | 1 | 0 | 0 | 0.03 |
| 8111 | Vidur Dasgupta | 1 | 1 | 0 | 0 | 0.03 |
| 8112 | Herr Heinfried Kraushaar | 1 | 0 | 9 | 2 | 0.03 |
| 8113 | Alison Nelson | 1 | 0 | 8 | 2 | 0.03 |
| 8114 | Eric Gomez | 1 | 0 | 8 | 2 | 0.03 |
| 8115 | Kimberly Stevens | 1 | 0 | 8 | 2 | 0.03 |
| 8116 | Xiuying Chen | 1 | 0 | 8 | 2 | 0.03 |
| 8117 | Bobby Hester | 1 | 0 | 11 | 1 | 0.02 |
| 8118 | Brian Holmes | 1 | 0 | 11 | 1 | 0.02 |
| 8119 | Jan Jaśko | 1 | 0 | 11 | 1 | 0.02 |
| 8120 | Konrad Szpyt | 1 | 0 | 11 | 1 | 0.02 |
| 8121 | Shari Gomez | 1 | 0 | 11 | 1 | 0.02 |
| 8122 | Freddy Dörr | 1 | 0 | 7 | 2 | 0.02 |
| 8123 | Gina Lehmann-Nohlmans | 1 | 0 | 7 | 2 | 0.02 |
| 8124 | Hans-Ludwig Käster | 1 | 0 | 7 | 2 | 0.02 |
| 8125 | Niels Hering | 1 | 0 | 7 | 2 | 0.02 |
| 8126 | Anni Bauer | 1 | 0 | 10 | 1 | 0.02 |
| 8127 | Cornelius Kabus | 1 | 0 | 10 | 1 | 0.02 |
| 8128 | Friedo Eberhardt | 1 | 0 | 10 | 1 | 0.02 |
| 8129 | Heinz-Josef Ritter | 1 | 0 | 10 | 1 | 0.02 |
| 8130 | Sepp Köhler | 1 | 0 | 10 | 1 | 0.02 |
| 8131 | Vadim Killer | 1 | 0 | 10 | 1 | 0.02 |
| 8132 | Amanda Davidson | 1 | 0 | 13 | 0 | 0.02 |
| 8133 | Barbara Hall | 1 | 0 | 13 | 0 | 0.02 |
| 8134 | Cassandra Norris | 1 | 0 | 13 | 0 | 0.02 |
| 8135 | Danielle Peters | 1 | 0 | 13 | 0 | 0.02 |
| 8136 | Katherine Castillo | 1 | 0 | 13 | 0 | 0.02 |
| 8137 | Kelli Rojas | 1 | 0 | 13 | 0 | 0.02 |
| 8138 | Mary Gonzalez | 1 | 0 | 13 | 0 | 0.02 |
| 8139 | Rebecca Taylor | 1 | 0 | 13 | 0 | 0.02 |
| 8140 | Tonya Andrews | 1 | 0 | 13 | 0 | 0.02 |
| 8141 | Casey Green | 1 | 0 | 9 | 1 | 0.02 |
| 8142 | Frau Sybille Becker | 1 | 0 | 9 | 1 | 0.02 |
| 8143 | Fritz Schuster | 1 | 0 | 9 | 1 | 0.02 |
| 8144 | John Goodwin | 1 | 0 | 9 | 1 | 0.02 |
| 8145 | Miranda Page | 1 | 0 | 9 | 1 | 0.02 |
| 8146 | Patricia Rodriguez | 1 | 0 | 9 | 1 | 0.02 |
| 8147 | Radmila Stey-Kambs | 1 | 0 | 9 | 1 | 0.02 |
| 8148 | Rick House | 1 | 0 | 9 | 1 | 0.02 |
| 8149 | Ronald Rice | 1 | 0 | 9 | 1 | 0.02 |
| 8150 | Susan Rogers | 1 | 0 | 9 | 1 | 0.02 |
| 8151 | Aarav Chada | 1 | 0 | 8 | 1 | 0.02 |
| 8152 | Jennifer Alexander | 1 | 0 | 8 | 1 | 0.02 |
| 8153 | Kristina Lang | 1 | 0 | 8 | 1 | 0.02 |
| 8154 | Lauren Steele | 1 | 0 | 8 | 1 | 0.02 |
| 8155 | Lori Young | 1 | 0 | 8 | 1 | 0.02 |
| 8156 | Sean Riggs | 1 | 0 | 8 | 1 | 0.02 |
| 8157 | Tiffany Cain | 1 | 0 | 8 | 1 | 0.02 |
| 8158 | Camilla Sontag | 1 | 0 | 7 | 1 | 0.02 |
| 8159 | Irmtrud Schmiedecke | 1 | 0 | 7 | 1 | 0.02 |
| 8160 | Rosalie Bonbach | 1 | 0 | 7 | 1 | 0.02 |
| 8161 | Shane Davis | 1 | 0 | 7 | 1 | 0.02 |
| 8162 | Xia Dong | 1 | 0 | 7 | 1 | 0.02 |
| 8163 | Adrien Gonzalez | 1 | 0 | 6 | 1 | 0.02 |
| 8164 | Anastasie Auger | 1 | 0 | 6 | 1 | 0.02 |
| 8165 | Georges-Grégoire Martin | 1 | 0 | 6 | 1 | 0.02 |
| 8166 | Bronze Tiger | 1 | 0 | 5 | 1 | 0.01 |
| 8167 | Bryce Webb | 1 | 0 | 5 | 1 | 0.01 |
| 8168 | Debra Richards | 1 | 0 | 5 | 1 | 0.01 |
| 8169 | Lisa Frost | 1 | 0 | 5 | 1 | 0.01 |
| 8170 | Michael Hall | 1 | 0 | 5 | 1 | 0.01 |
| 8171 | Andrew Oneill | 1 | 0 | 8 | 0 | 0.01 |
| 8172 | Beth Walters | 1 | 0 | 8 | 0 | 0.01 |
| 8173 | Jacob Wiek | 1 | 0 | 8 | 0 | 0.01 |
| 8174 | Jennifer Ruiz | 1 | 0 | 8 | 0 | 0.01 |
| 8175 | Nina Anders | 1 | 0 | 8 | 0 | 0.01 |
| 8176 | Rachel Luna | 1 | 0 | 8 | 0 | 0.01 |
| 8177 | Regina Watkins | 1 | 0 | 8 | 0 | 0.01 |
| 8178 | Sandra Holden | 1 | 0 | 8 | 0 | 0.01 |
| 8179 | Tabitha Jones | 1 | 0 | 8 | 0 | 0.01 |
| 8180 | Tyler Austin | 1 | 0 | 8 | 0 | 0.01 |
| 8181 | Alex Hernandez | 1 | 0 | 4 | 1 | 0.01 |
| 8182 | Cesar Nguyen | 1 | 0 | 4 | 1 | 0.01 |
| 8183 | Elizabeth Donaldson | 1 | 0 | 4 | 1 | 0.01 |
| 8184 | Kevin Russell | 1 | 0 | 4 | 1 | 0.01 |
| 8185 | Stanley Perez | 1 | 0 | 4 | 1 | 0.01 |
| 8186 | Sydney Mack | 1 | 0 | 4 | 1 | 0.01 |
| 8187 | Kristina Jones | 1 | 0 | 7 | 0 | 0.01 |
| 8188 | Claudia Cunningham | 1 | 0 | 3 | 1 | 0.01 |
| 8189 | James Palmer | 1 | 0 | 3 | 1 | 0.01 |
| 8190 | Janina Gronkiewicz | 1 | 0 | 3 | 1 | 0.01 |
| 8191 | Phillip Barnes | 1 | 0 | 3 | 1 | 0.01 |
| 8192 | Robert Hughes | 1 | 0 | 3 | 1 | 0.01 |
| 8193 | Tao Xue | 1 | 0 | 6 | 0 | 0.01 |
| 8194 | Jennifer Moore | 1 | 0 | 2 | 1 | 0.01 |
| 8195 | Benjamin Gutierrez | 1 | 0 | 5 | 0 | 0.01 |
| 8196 | Bradley Valencia | 1 | 0 | 5 | 0 | 0.01 |
| 8197 | Brittany Sanchez | 1 | 0 | 5 | 0 | 0.01 |
| 8198 | Charlene Collins | 1 | 0 | 5 | 0 | 0.01 |
| 8199 | Elizabeth Brennan | 1 | 0 | 5 | 0 | 0.01 |
| 8200 | Jason Davis | 1 | 0 | 5 | 0 | 0.01 |
| 8201 | Lisa Sparks | 1 | 0 | 5 | 0 | 0.01 |
| 8202 | Maria Rubio | 1 | 0 | 5 | 0 | 0.01 |
| 8203 | Patrick Wall | 1 | 0 | 5 | 0 | 0.01 |
| 8204 | Timothy Sanchez | 1 | 0 | 5 | 0 | 0.01 |
| 8205 | Andean Horizon | 1 | 0 | 4 | 0 | 0.01 |
| 8206 | B.D. Wolf | 1 | 0 | 4 | 0 | 0.01 |
| 8207 | Connor Juarez | 1 | 0 | 4 | 0 | 0.01 |
| 8208 | Darren Pineda | 1 | 0 | 4 | 0 | 0.01 |
| 8209 | Dishani Sundaram | 1 | 0 | 4 | 0 | 0.01 |
| 8210 | Doris Klemt-Junck | 1 | 0 | 4 | 0 | 0.01 |
| 8211 | Eon | 1 | 0 | 4 | 0 | 0.01 |
| 8212 | Gokul Kapur | 1 | 0 | 4 | 0 | 0.01 |
| 8213 | Indrans Vyas | 1 | 0 | 4 | 0 | 0.01 |
| 8214 | Isabella Johnson | 1 | 0 | 4 | 0 | 0.01 |
| 8215 | James Weber | 1 | 0 | 4 | 0 | 0.01 |
| 8216 | Jing Bai | 1 | 0 | 4 | 0 | 0.01 |
| 8217 | Lei Hao | 1 | 0 | 4 | 0 | 0.01 |
| 8218 | Lucas Smith | 1 | 0 | 4 | 0 | 0.01 |
| 8219 | Mark Dunlap | 1 | 0 | 4 | 0 | 0.01 |
| 8220 | Melissa Douglas | 1 | 0 | 4 | 0 | 0.01 |
| 8221 | Philippine Colin | 1 | 0 | 4 | 0 | 0.01 |
| 8222 | Riaan Kalla | 1 | 0 | 4 | 0 | 0.01 |
| 8223 | Saira Kala | 1 | 0 | 4 | 0 | 0.01 |
| 8224 | Sean Cameron | 1 | 0 | 4 | 0 | 0.01 |
| 8225 | Shota Suzuki | 1 | 0 | 4 | 0 | 0.01 |
| 8226 | The Hollow Vestige | 1 | 0 | 4 | 0 | 0.01 |
| 8227 | William Smith | 1 | 0 | 4 | 0 | 0.01 |
| 8228 | Elizabeth Leon | 1 | 0 | 3 | 0 | 0.01 |
| 8229 | Gregory Kane | 1 | 0 | 3 | 0 | 0.01 |
| 8230 | Günther Mude | 1 | 0 | 3 | 0 | 0.01 |
| 8231 | Jessica Coleman | 1 | 0 | 3 | 0 | 0.01 |
| 8232 | Joerg Weiß | 1 | 0 | 3 | 0 | 0.01 |
| 8233 | Kim Bishop | 1 | 0 | 3 | 0 | 0.01 |
| 8234 | Manuel Roberts | 1 | 0 | 3 | 0 | 0.01 |
| 8235 | Megan Stephenson | 1 | 0 | 3 | 0 | 0.01 |
| 8236 | Michele Orozco | 1 | 0 | 3 | 0 | 0.01 |
| 8237 | Molly Whitaker | 1 | 0 | 3 | 0 | 0.01 |
| 8238 | PRVISE | 1 | 0 | 3 | 0 | 0.01 |
| 8239 | Patricia Jackson | 1 | 0 | 3 | 0 | 0.01 |
| 8240 | Peter Byrd | 1 | 0 | 3 | 0 | 0.01 |
| 8241 | Reginald Stumpf | 1 | 0 | 3 | 0 | 0.01 |
| 8242 | William Ashley | 1 | 0 | 3 | 0 | 0.01 |
| 8243 | Alicia Simmons | 1 | 0 | 2 | 0 | 0.00 |
| 8244 | Anne Lefebvre | 1 | 0 | 2 | 0 | 0.00 |
| 8245 | Christopher Conway | 1 | 0 | 2 | 0 | 0.00 |
| 8246 | Dominique Letellier | 1 | 0 | 2 | 0 | 0.00 |
| 8247 | Heidi Dudley | 1 | 0 | 2 | 0 | 0.00 |
| 8248 | Isaac Brown | 1 | 0 | 2 | 0 | 0.00 |
| 8249 | Jonathan Morris | 1 | 0 | 2 | 0 | 0.00 |
| 8250 | Kimberly Walker | 1 | 0 | 2 | 0 | 0.00 |
| 8251 | Kristen Lucero | 1 | 0 | 2 | 0 | 0.00 |
| 8252 | Samantha Mcneil | 1 | 0 | 2 | 0 | 0.00 |
| 8253 | William Torres | 1 | 0 | 2 | 0 | 0.00 |
| 8254 | Echelon | 1 | 0 | 1 | 0 | 0.00 |
| 8255 | Gudula Riehl | 1 | 0 | 1 | 0 | 0.00 |
| 8256 | Helmtrud Mälzer-Paffrath | 1 | 0 | 1 | 0 | 0.00 |
| 8257 | Michael Potts | 1 | 0 | 1 | 0 | 0.00 |
| 8258 | Ping Duan | 1 | 0 | 1 | 0 | 0.00 |
| 8259 | Yang Tao | 1 | 0 | 1 | 0 | 0.00 |
| 8260 | John Hayes | 1 | 0 | 0 | 0 | 0.00 |
| 8261 | Jędrzej Przeniosło | 1 | 0 | 0 | 0 | 0.00 |
6.2 Question 3a) Visualize the careers of three artists. Compare and contrast their rise in popularity and influence?
Based on the results of the analysis above, the top artists in each category will be selected.
- Greatest Number of Music Released: Sailor Shift
- Most Popular Artist (Highest Number of Notable Hits): Jay Walters
- Most Influential Artist (Influence Artists and Collaborations), Most Music Influence & Highest Star Factor: Min Fu
Show Code
# Extract all creators' relevant data for scaling
all_scaled_data <- creator_rankings %>%
select(total_songs, notable_hits, collaboration_influence_creator, influence_music)
# Scale all columns to 0–100
all_scaled <- as.data.frame(lapply(all_scaled_data, scales::rescale, to = c(0, 100)))
rownames(all_scaled) <- creator_rankings$creator_name
chosen_creator_1 = "Sailor Shift"
# Filter the data for Sailor Shift
creator_1_data <- creator_rankings %>%
filter(creator_name == chosen_creator_1) %>%
select(total_songs, notable_hits, collaboration_influence_creator, influence_music)
# Extract scaled values for Sailor Shift
creator_1_scaled <- all_scaled[chosen_creator_1, , drop = FALSE]
# Construct radar input with min and max for the chart frame
radar_matrix_1 <- rbind(
rep(100, ncol(creator_1_scaled)), # Max values
rep(0, ncol(creator_1_scaled)), # Min values
creator_1_scaled # Actual values
)
# Plot Radar Chart
par(mar = c(2, 2, 4, 2), oma = c(1, 1, 3, 1))
radarchart(radar_matrix_1,
axistype = 1,
pcol = "#0027EA",
pfcol = adjustcolor("#0027EA", alpha.f = 0.3),
plwd = 2,
cglcol = "grey",
cglty = 1,
cglwd = 0.8,
axislabcol = "black",
caxislabels = paste0(seq(0, 100, 25), "%"),
vlcex = 0.85,
title = paste("Star Profile: ", chosen_creator_1),
calcex = 0.8,
cex.main = 1.3,
vlabels = c("Total Music", "Notable\nHits", "Artist Influ & Colab", "Music\nInfluenced"),
centerzero = TRUE)
Show Code
chosen_creator_2 = "Jay Walters"
# Filter the data for Sailor Shift
creator_2_data <- creator_rankings %>%
filter(creator_name == chosen_creator_2) %>%
select(total_songs, notable_hits, collaboration_influence_creator, influence_music)
# Extract scaled values for Sailor Shift
creator_2_scaled <- all_scaled[chosen_creator_2, , drop = FALSE]
# Construct radar input with min and max for the chart frame
radar_matrix_2 <- rbind(
rep(100, ncol(creator_2_scaled)), # Max values
rep(0, ncol(creator_2_scaled)), # Min values
creator_2_scaled # Actual values
)
# Plot Radar Chart
par(mar = c(2, 2, 4, 2), oma = c(1, 1, 3, 1))
radarchart(radar_matrix_2,
axistype = 1,
pcol = "#FF5757",
pfcol = adjustcolor("#FF5757", alpha.f = 0.3),
plwd = 2,
cglcol = "grey",
cglty = 1,
cglwd = 0.8,
axislabcol = "black",
caxislabels = paste0(seq(0, 100, 25), "%"),
vlcex = 0.85,
title = paste("Star Profile: ", chosen_creator_2),
calcex = 0.8,
cex.main = 1.3,
vlabels = c("Total Music", "Notable\nHits", "Artist Influ & Colab", "Music\nInfluenced"),
centerzero = TRUE)
Show Code
chosen_creator_3 = "Min Fu"
# Filter the data for Sailor Shift
creator_3_data <- creator_rankings %>%
filter(creator_name == chosen_creator_3) %>%
select(total_songs, notable_hits, collaboration_influence_creator, influence_music)
# Extract scaled values for Sailor Shift
creator_3_scaled <- all_scaled[chosen_creator_3, , drop = FALSE]
# Construct radar input with min and max for the chart frame
radar_matrix_3 <- rbind(
rep(100, ncol(creator_3_scaled)), # Max values
rep(0, ncol(creator_3_scaled)), # Min values
creator_3_scaled # Actual values
)
# Plot Radar Chart
par(mar = c(2, 2, 4, 2), oma = c(1, 1, 3, 1))
radarchart(radar_matrix_3,
axistype = 1,
pcol = "#A45200",
pfcol = adjustcolor("#A45200", alpha.f = 0.3),
plwd = 2,
cglcol = "grey",
cglty = 1,
cglwd = 0.8,
axislabcol = "black",
caxislabels = paste0(seq(0, 100, 25), "%"),
vlcex = 0.85,
title = paste("Star Profile: ", chosen_creator_3),
calcex = 0.8,
cex.main = 1.3,
vlabels = c("Total Music", "Notable\nHits", "Artist Influ & Colab", "Music\nInfluenced"),
centerzero = TRUE)
6.2.1 Visualizing the career of Sailor Shift
Sailor Shift has released the most number of music (Song/Album).
Show Code
# Data Preparation
chosen_creator_1 = "Sailor Shift"
# Step 1: Get the node of the chosen creator
chosen_node_1 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1) %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the top creator produced
creator_songs_1 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
creators_songs_collaborate_influence_1 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1,
infuence_music_collaborate != chosen_node_1) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
creators_songs_influence_1 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1,
infuence_music_collaborate != chosen_node_1,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
creators_songs_influence_creators_1 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1,
influence_creator != chosen_node_1,
!is.na(influence_creator),
infuence_music_collaborate %in% creators_songs_influence_1) %>%
pull(influence_creator)
all_nodes <- unique(c(chosen_node_1,
creator_songs_1,
creators_songs_collaborate_influence_1,
creators_songs_influence_creators_1))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == chosen_creator_1, 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == chosen_creator_1, chosen_creator_1, NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)Show Code
# Data Preparation
# Step 1: Count number of music by release date
music_by_date_1 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_1)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = music_by_date_1,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of notable music by release date
notable_music_by_date_1 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_1), notable == TRUE) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = notable_music_by_date_1,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Notable Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced artists by release date
influence_artists_by_date_1 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% unique(chosen_node_1),
influence_creator != unique(chosen_node_1)) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "music_count") %>%
arrange(first_influence_date) %>%
rename(creator_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_artists_by_date_1,
x = ~creator_release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_song_by_date_1 <- mc1_nodes_clean %>%
filter(name %in% unique(creators_songs_influence_1)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_song_by_date_1,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Music",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)
Note
Sailor Shift has no influence on Music creation
6.2.2 Visualizing the career of Jay Walters
Jay Walters has the highest number of notable hits.
Show Code
# Data Preparation
chosen_creator_2 = "Jay Walters"
# Step 1: Get the node of the chosen creator
chosen_node_2 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2) %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the top creator produced
creator_songs_2 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
creators_songs_collaborate_influence_2 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
creators_songs_influence_2 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
creators_songs_influence_creators_2 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2,
influence_creator != chosen_node_1,
!is.na(influence_creator),
infuence_music_collaborate %in% creators_songs_influence_2) %>%
pull(influence_creator)
all_nodes <- unique(c(chosen_node_2,
creator_songs_2,
creators_songs_collaborate_influence_2,
creators_songs_influence_creators_2))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == chosen_creator_2, 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == chosen_creator_2, chosen_creator_2, NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)Show Code
# Data Preparation
# Step 1: Count number of music by release date
music_by_date_2 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_2)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = music_by_date_2,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of notable music by release date
notable_music_by_date_2 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_2), notable == TRUE) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = notable_music_by_date_2,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Notable Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced artists by release date
influence_artists_by_date_2 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% unique(chosen_node_2),
influence_creator != unique(chosen_node_2)) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "music_count") %>%
arrange(first_influence_date) %>%
rename(creator_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_artists_by_date_2,
x = ~creator_release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_song_by_date_2 <- mc1_nodes_clean %>%
filter(name %in% unique(creators_songs_influence_2)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_song_by_date_2,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Music",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)6.2.3 Visualizing the career of Min Fu
Min Fu is the most influential artist.
Show Code
# Data Preparation
chosen_creator_3 = "Min Fu"
# Step 1: Get the node of the chosen creator
chosen_node_3 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3) %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the top creator produced
creator_songs_3 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
creators_songs_collaborate_influence_3 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3,
infuence_music_collaborate != chosen_node_3) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
creators_songs_influence_3 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3,
infuence_music_collaborate != chosen_node_3,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
creators_songs_influence_creators_3 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3,
influence_creator != chosen_node_3,
!is.na(influence_creator),
infuence_music_collaborate %in% creators_songs_influence_3) %>%
pull(influence_creator)
all_nodes <- unique(c(chosen_node_3,
creator_songs_3,
creators_songs_collaborate_influence_3,
creators_songs_influence_creators_3))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == chosen_creator_3, 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == chosen_creator_3, chosen_creator_3, NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)Show Code
# Data Preparation
# Step 1: Count number of music by release date
music_by_date_3 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_3)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = music_by_date_3,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of notable music by release date
notable_music_by_date_3 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_3), notable == TRUE) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = notable_music_by_date_3,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Notable Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced artists by release date
influence_artists_by_date_3 <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% unique(chosen_node_3),
influence_creator != unique(chosen_node_3)) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "music_count") %>%
arrange(first_influence_date) %>%
rename(creator_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_artists_by_date_3,
x = ~creator_release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_song_by_date_3 <- mc1_nodes_clean %>%
filter(name %in% unique(creators_songs_influence_3)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_song_by_date_3,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Music",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)6.2.4 Compare and contrast the three artists’ rise in popularity and influence
The cumulative graphs of the 3 artists (Sailor Shift, Jay Walters and Min Fu) will be overlaid for comparison of their musical careers.
Show Code
# Visualisation
plot_ly(
data = music_by_date_1,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_1,
line = list(color = "#2E3192", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_1,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = music_by_date_2,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_2,
line = list(color = "green", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_2,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = music_by_date_3,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_3,
line = list(color = "purple", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_3,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Visualisation
plot_ly(
data = notable_music_by_date_1,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_1,
line = list(color = "#2E3192", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_1,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = notable_music_by_date_2,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_2,
line = list(color = "green", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_2,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = notable_music_by_date_3,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_3,
line = list(color = "purple", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_3,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Visualisation
plot_ly(
data = influence_artists_by_date_1,
x = ~creator_release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_1,
line = list(color = "#2E3192", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_1,
"<br>Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_artists_by_date_2,
x = ~creator_release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_2,
line = list(color = "green", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_2,
"<br>Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_artists_by_date_3,
x = ~creator_release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_3,
line = list(color = "purple", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_3,
"<br>Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)
Note
Sailor Shift has only Collaborations and no Artist Influence
Show Code
# Visualisation
plot_ly(
data = influence_song_by_date_1,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_1,
line = list(color = "#2E3192", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_1,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_song_by_date_2,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_2,
line = list(color = "green", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_2,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_song_by_date_3,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_3,
line = list(color = "purple", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_3,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)
Note
Sailor Shift has no influence on music creation
Visualize the careers of three artists. Compare and contrast their rise in popularity and influence?
- Among the three artists, Sailor Shift is the most recent entrant to the music industry, having debuted in 2024.
- She maintained consistent music releases through 2040.
- With 38 total releases, she surpassed Jay Walters’ record (37 releases) in 2040, establishing herself as the most prolific artist.
- Min Fu has 12 records.
- While Sailor Shift has released more music than Jay Walters, Jay Walters is the most popular Artist having released 35 hits that made the top record chart.
- Sailor Shift has 25 hits while Min Fu has 12.
- Min Fu is the most influential artist having influenced/collaborated with 598 artists and influenced the creation of 192 music.
- Jay Walters has a much lower influence having influence/collaborated with 51 artists and 50 music.
- Sailor Shift has a similar influence of 48 artists (all collaborations) but 0 influence on the music scene.
- However, Sailor Shift has the most recent influence, with new artist connections as recent as 2040.
- In contrast, Jay Walters’ influence period ended earlier (last connection in 2035), while Min Fu’s influence dates back to 2030.
6.3 Question 3b) Using this characterization, give three predictions of who the next Oceanus Folk stars with be over the next five years.
This will be a continuation of Question 3a where only Oceanus Folk artists and the Oceanus Folk songs that they have produced are analysed.
6.3.1 Analysing the careers of all Oceanus Folk Artists
In order to predict the next Oceanus Folk stars, a grading rubric will be used where their ranking in these 4 categories (Number of Music released, Number of Notable Music, Number of New Artists Influenced / Collaborated With and Number of Music influenced). Each category will be given equal weighting with a maximum score of 4 and the Oceanus Folk artists will be ranked using this rubric.
Show Code
genre_creators = creator_and_songs_and_influences_and_creators_collaborate %>%
filter(song_genre == "Oceanus Folk") %>%
pull(creator_from)
# Step 1: Filter to only Oceanus Folk Artists
oceanus_creator_and_songs_and_influences_and_creators_collaborate <- creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% genre_creators, song_genre == "Oceanus Folk")
# Step 2: To highlight songs that the creator influence that is not produced by same creator
oceanus_creator_influence_lists <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
group_by(creator_name, creator_node_type, song_to, song_name, creator_release_date, song_genre, notable) %>%
distinct () %>%
summarize(
unique_collaborate = list(unique(na.omit(infuence_music_collaborate[creator_from != influence_creator & `Edge Colour` == "Creator Of"]))),
unique_influence_creators = list(unique(na.omit(influence_creator[creator_from != influence_creator & `Edge Colour` == "Influenced By"]))),
unique_influence_music = list(unique(na.omit(infuence_music_collaborate[creator_from != influence_creator & !is.na(influence_genre)])))
)
# Step 3: Aggregate unique influences per creator
oceanus_creator_stats <- oceanus_creator_influence_lists %>%
group_by(creator_name) %>%
summarize(
total_songs = n_distinct(song_to),
notable_hits = sum(notable == TRUE, na.rm = TRUE),
collaboration = length(unique(unlist(unique_collaborate))),
influence_creators = length(unique(unlist(unique_influence_creators))),
collaboration_influence_creator = length(unique(c(unlist(unique_influence_creators),unlist( unique_collaborate)))),
influence_music = length(unique(unlist(unique_influence_music)))
)
# Step 4: Create Scoring Rubric
oceanus_creator_rankings <- oceanus_creator_stats %>%
mutate(
# Normalize each metric (0-1 scale)
songs_score = (total_songs - min(total_songs)) / (max(total_songs) - min(total_songs)),
notable_score = (notable_hits - min(notable_hits)) / (max(notable_hits) - min(notable_hits)),
artists_score = (collaboration_influence_creator - min(collaboration_influence_creator)) / (max(collaboration_influence_creator) - min(collaboration_influence_creator)),
music_score = (influence_music - min(influence_music)) / (max(influence_music) - min(influence_music)),
# Calculate composite score (equal weighting)
composite_score = songs_score + notable_score + artists_score + music_score
) %>%
arrange(desc(composite_score)) %>%
select(creator_name, total_songs, notable_hits, collaboration_influence_creator, influence_music,
composite_score)
# Final Ranked Table
oceanus_creator_rankings %>%
mutate(
Rank = row_number(),
`Star Factor` = round(composite_score, 3)
) %>%
select(Rank, creator_name, total_songs, notable_hits, collaboration_influence_creator,
influence_music, `Star Factor`) %>%
rename(
`Artist` = creator_name,
`Total Music` = total_songs,
`Notable Hits` = notable_hits,
`Artist Influ & Colab` = collaboration_influence_creator,
`Music Influenced` = influence_music
) %>%
kable(caption = "Oceanus Folk Artists Ranked by Star Factor") %>%
kable_styling("striped", full_width = F) %>%
scroll_box(height = "300px")| Rank | Artist | Total Music | Notable Hits | Artist Influ & Colab | Music Influenced | Star Factor |
|---|---|---|---|---|---|---|
| 1 | Sailor Shift | 36 | 24 | 41 | 0 | 2.216 |
| 2 | Chao Wu | 4 | 3 | 190 | 44 | 2.211 |
| 3 | Xia Jia | 4 | 3 | 178 | 42 | 2.102 |
| 4 | Donna Caldwell | 2 | 1 | 170 | 41 | 1.897 |
| 5 | Xiulan Ye | 2 | 1 | 170 | 41 | 1.897 |
| 6 | Sandra Smith | 1 | 0 | 162 | 39 | 1.739 |
| 7 | Zacharie Martins | 4 | 4 | 136 | 32 | 1.695 |
| 8 | Constance Guibert | 3 | 3 | 117 | 28 | 1.434 |
| 9 | Ignazio Pastine | 3 | 3 | 117 | 28 | 1.434 |
| 10 | Embers of Wrath | 1 | 1 | 107 | 26 | 1.196 |
| 11 | Ann Holland | 1 | 1 | 99 | 23 | 1.085 |
| 12 | Eric Beasley | 1 | 1 | 99 | 23 | 1.085 |
| 13 | Jun Han | 2 | 2 | 98 | 20 | 1.082 |
| 14 | Chao Tan | 4 | 4 | 85 | 15 | 1.041 |
| 15 | Filippo Pelli | 5 | 4 | 77 | 15 | 1.027 |
| 16 | Lei Wan | 1 | 1 | 95 | 20 | 0.996 |
| 17 | Tao Ren | 1 | 1 | 95 | 20 | 0.996 |
| 18 | Yesenia Miller | 1 | 1 | 95 | 20 | 0.996 |
| 19 | Lei Tan | 2 | 2 | 76 | 13 | 0.807 |
| 20 | Isabella Farinelli | 3 | 2 | 65 | 13 | 0.778 |
| 21 | Yang Yao | 3 | 2 | 63 | 12 | 0.745 |
| 22 | Gang Tao | 1 | 1 | 71 | 13 | 0.711 |
| 23 | Li Qiu | 1 | 1 | 71 | 13 | 0.711 |
| 24 | Min He | 1 | 1 | 71 | 13 | 0.711 |
| 25 | Ping Yan | 1 | 1 | 71 | 13 | 0.711 |
| 26 | Wei Ma | 1 | 1 | 71 | 13 | 0.711 |
| 27 | Na Ren | 3 | 3 | 50 | 10 | 0.673 |
| 28 | Alfred Thibault | 3 | 3 | 35 | 11 | 0.616 |
| 29 | Synaptic Stream | 3 | 3 | 35 | 11 | 0.616 |
| 30 | Zoé-Agnès Delaunay | 3 | 3 | 35 | 11 | 0.616 |
| 31 | Wei Gao | 2 | 2 | 48 | 11 | 0.615 |
| 32 | Chao Qiao | 2 | 2 | 52 | 10 | 0.613 |
| 33 | Jun Xu | 2 | 2 | 52 | 10 | 0.613 |
| 34 | Vanessa Ramos | 2 | 2 | 47 | 9 | 0.564 |
| 35 | Lei Zeng | 2 | 1 | 47 | 10 | 0.545 |
| 36 | Drowned Harbor | 12 | 5 | 4 | 0 | 0.544 |
| 37 | Ivy Echos | 11 | 4 | 13 | 1 | 0.544 |
| 38 | Orla Seabloom | 8 | 8 | 0 | 0 | 0.533 |
| 39 | Adriana Figueroa | 1 | 1 | 49 | 10 | 0.527 |
| 40 | Charles Hall | 1 | 1 | 49 | 10 | 0.527 |
| 41 | Fang Wu | 1 | 1 | 49 | 10 | 0.527 |
| 42 | James Mosley | 1 | 1 | 49 | 10 | 0.527 |
| 43 | Thomas Dudley | 1 | 1 | 49 | 10 | 0.527 |
| 44 | Tao Yao | 3 | 3 | 43 | 5 | 0.522 |
| 45 | Juan Yu | 3 | 3 | 34 | 7 | 0.520 |
| 46 | Lei Jin | 3 | 3 | 34 | 7 | 0.520 |
| 47 | Yong Lai | 3 | 3 | 34 | 7 | 0.520 |
| 48 | Yong Shen | 3 | 3 | 34 | 7 | 0.520 |
| 49 | Guiying Dai | 1 | 1 | 46 | 10 | 0.511 |
| 50 | Yong Chen | 1 | 1 | 46 | 10 | 0.511 |
| 51 | Juan Duan | 1 | 1 | 46 | 9 | 0.488 |
| 52 | Tao Ye | 1 | 1 | 46 | 9 | 0.488 |
| 53 | Yong Guo | 1 | 1 | 46 | 9 | 0.488 |
| 54 | Lei Shen | 2 | 2 | 36 | 8 | 0.483 |
| 55 | Xia Cui | 2 | 2 | 36 | 8 | 0.483 |
| 56 | Xiuying Li | 2 | 2 | 36 | 8 | 0.483 |
| 57 | Qiang Song | 3 | 3 | 35 | 5 | 0.480 |
| 58 | Beatrice Albright | 7 | 7 | 3 | 0 | 0.479 |
| 59 | Daniel O'Connell | 7 | 7 | 3 | 0 | 0.479 |
| 60 | Copper Canyon Ghosts | 7 | 7 | 2 | 0 | 0.474 |
| 61 | Jie Cui | 3 | 3 | 25 | 6 | 0.450 |
| 62 | Tao Jin | 4 | 4 | 24 | 3 | 0.447 |
| 63 | Yong Dong | 4 | 4 | 24 | 3 | 0.447 |
| 64 | The Tide Singer's Knot | 8 | 4 | 6 | 1 | 0.421 |
| 65 | The Saltwater Weavers | 9 | 4 | 4 | 0 | 0.416 |
| 66 | Min Jin | 2 | 2 | 27 | 7 | 0.413 |
| 67 | Ming Chen | 1 | 1 | 36 | 8 | 0.413 |
| 68 | Lisa Martin | 2 | 2 | 30 | 6 | 0.406 |
| 69 | Monica Nelson | 2 | 2 | 30 | 6 | 0.406 |
| 70 | Guglielmo Canetta | 3 | 3 | 16 | 6 | 0.403 |
| 71 | Nicola Bernetti | 3 | 3 | 16 | 6 | 0.403 |
| 72 | Serena Lettiere | 3 | 3 | 16 | 6 | 0.403 |
| 73 | Vincentio Gentili | 3 | 3 | 16 | 6 | 0.403 |
| 74 | Sophie Ramirez | 5 | 5 | 15 | 0 | 0.402 |
| 75 | Maya Jensen | 5 | 5 | 12 | 0 | 0.386 |
| 76 | Georgina Piñol-Guerra | 1 | 0 | 43 | 7 | 0.385 |
| 77 | Lalo Salgado Cazorla | 1 | 0 | 43 | 7 | 0.385 |
| 78 | Luigina Stoppani-Sandi | 1 | 0 | 43 | 7 | 0.385 |
| 79 | Tao Lei | 2 | 2 | 30 | 5 | 0.383 |
| 80 | The Brine Choir | 7 | 4 | 6 | 0 | 0.370 |
| 81 | Aneta Pruschke-Sölzer | 2 | 2 | 23 | 6 | 0.369 |
| 82 | Cesare Cicilia | 2 | 2 | 23 | 6 | 0.369 |
| 83 | Courtney Phillips | 1 | 1 | 32 | 7 | 0.369 |
| 84 | Jennifer Diaz | 1 | 1 | 32 | 7 | 0.369 |
| 85 | Kelli Turner | 1 | 1 | 32 | 7 | 0.369 |
| 86 | Latasha Chavez | 1 | 1 | 32 | 7 | 0.369 |
| 87 | Min Qian | 1 | 1 | 32 | 7 | 0.369 |
| 88 | Na Wen | 3 | 3 | 21 | 3 | 0.361 |
| 89 | Thibault Hardy | 2 | 2 | 21 | 6 | 0.359 |
| 90 | Coralia Bellweather | 5 | 5 | 6 | 0 | 0.354 |
| 91 | Bryan Smith | 1 | 1 | 33 | 6 | 0.352 |
| 92 | Emily Jackson | 1 | 1 | 33 | 6 | 0.352 |
| 93 | Gregory Williams | 1 | 1 | 33 | 6 | 0.352 |
| 94 | Ronald Kennedy | 1 | 1 | 33 | 6 | 0.352 |
| 95 | Adèle Bonneau | 2 | 2 | 19 | 6 | 0.348 |
| 96 | James Clark | 1 | 1 | 30 | 6 | 0.336 |
| 97 | Kristin Anderson | 1 | 1 | 30 | 6 | 0.336 |
| 98 | Ming Su | 1 | 1 | 30 | 6 | 0.336 |
| 99 | Guiying Liao | 2 | 2 | 18 | 5 | 0.320 |
| 100 | Ping Sun | 2 | 2 | 18 | 5 | 0.320 |
| 101 | Yan Zou | 2 | 2 | 18 | 5 | 0.320 |
| 102 | Jie Dai | 1 | 1 | 27 | 6 | 0.320 |
| 103 | Juan Gu | 1 | 1 | 27 | 6 | 0.320 |
| 104 | Ping Pan | 1 | 1 | 27 | 6 | 0.320 |
| 105 | Qiang Dai | 1 | 1 | 27 | 6 | 0.320 |
| 106 | Tao Chang | 1 | 1 | 27 | 6 | 0.320 |
| 107 | Xiulan He | 1 | 1 | 27 | 6 | 0.320 |
| 108 | Na Yang | 2 | 2 | 25 | 3 | 0.312 |
| 109 | Lauretta Tresoldi | 2 | 2 | 20 | 4 | 0.308 |
| 110 | Xiulan Xu | 2 | 2 | 17 | 4 | 0.292 |
| 111 | Wei Guo | 2 | 2 | 21 | 3 | 0.291 |
| 112 | Levi Holloway | 4 | 4 | 7 | 0 | 0.289 |
| 113 | Jie Li | 2 | 2 | 20 | 3 | 0.285 |
| 114 | Tao Dai | 2 | 2 | 20 | 3 | 0.285 |
| 115 | Jonah Calloway | 4 | 4 | 6 | 0 | 0.284 |
| 116 | Marin Thorne | 4 | 4 | 6 | 0 | 0.284 |
| 117 | Alphons Donati-Pederiva | 2 | 2 | 19 | 3 | 0.280 |
| 118 | Augusto Villaverde Armengol | 2 | 2 | 19 | 3 | 0.280 |
| 119 | Feliciano Pizarro Moll | 2 | 2 | 19 | 3 | 0.280 |
| 120 | Juan Dong | 2 | 2 | 19 | 3 | 0.280 |
| 121 | Jing Long | 1 | 1 | 28 | 4 | 0.280 |
| 122 | Tao Qin | 1 | 1 | 28 | 4 | 0.280 |
| 123 | Xiuying Xiang | 1 | 1 | 28 | 4 | 0.280 |
| 124 | Yan Feng | 1 | 1 | 28 | 4 | 0.280 |
| 125 | Barnaby Quill | 4 | 4 | 4 | 0 | 0.273 |
| 126 | Jonas Fenwick | 4 | 4 | 4 | 0 | 0.273 |
| 127 | Marina Grey | 4 | 4 | 4 | 0 | 0.273 |
| 128 | Orin Caldwell | 4 | 4 | 4 | 0 | 0.273 |
| 129 | Selena Marrow | 4 | 4 | 4 | 0 | 0.273 |
| 130 | Silas Finch | 4 | 4 | 4 | 0 | 0.273 |
| 131 | Thorne Rivenhall | 4 | 4 | 4 | 0 | 0.273 |
| 132 | Brandy Reyes | 1 | 1 | 26 | 4 | 0.269 |
| 133 | Juan Qiao | 1 | 1 | 26 | 4 | 0.269 |
| 134 | Jun Jin | 1 | 1 | 26 | 4 | 0.269 |
| 135 | Laura Gibbs | 1 | 1 | 26 | 4 | 0.269 |
| 136 | Mary Medina | 1 | 1 | 26 | 4 | 0.269 |
| 137 | Na Ma | 1 | 1 | 26 | 4 | 0.269 |
| 138 | Raymond Mccoy | 1 | 1 | 26 | 4 | 0.269 |
| 139 | Rhonda Brown | 1 | 1 | 26 | 4 | 0.269 |
| 140 | Xiulan Ren | 1 | 1 | 26 | 4 | 0.269 |
| 141 | Na Peng | 2 | 1 | 29 | 2 | 0.268 |
| 142 | Gang Zhu | 2 | 2 | 21 | 2 | 0.268 |
| 143 | Ming Yu | 2 | 2 | 21 | 2 | 0.268 |
| 144 | Jing Zhong | 2 | 2 | 15 | 3 | 0.259 |
| 145 | Albert Miller | 2 | 2 | 19 | 2 | 0.257 |
| 146 | Adrien Weiss | 1 | 1 | 23 | 4 | 0.254 |
| 147 | Charles du Perez | 1 | 1 | 23 | 4 | 0.254 |
| 148 | Pauline Guyot de la Maillet | 1 | 1 | 23 | 4 | 0.254 |
| 149 | Qiang Qian | 2 | 2 | 18 | 2 | 0.252 |
| 150 | Walter White | 2 | 2 | 18 | 2 | 0.252 |
| 151 | Xia Xia | 2 | 2 | 18 | 2 | 0.252 |
| 152 | Édouard-Rémy Clerc | 1 | 1 | 18 | 5 | 0.250 |
| 153 | Qiang Xie | 2 | 2 | 17 | 2 | 0.247 |
| 154 | Xiuying Huang | 2 | 2 | 17 | 2 | 0.247 |
| 155 | Chao Xiao | 2 | 2 | 16 | 2 | 0.242 |
| 156 | Laetitia Petitjean | 2 | 2 | 11 | 3 | 0.238 |
| 157 | Madeleine Pineau | 2 | 2 | 11 | 3 | 0.238 |
| 158 | Susan Da Silva | 2 | 2 | 11 | 3 | 0.238 |
| 159 | Émilie Maillet | 2 | 2 | 11 | 3 | 0.238 |
| 160 | Antonietta Zamengo-Zanazzo | 1 | 1 | 20 | 4 | 0.238 |
| 161 | Patrizio Antonello-Salvemini | 1 | 1 | 20 | 4 | 0.238 |
| 162 | Xiulan Mo | 3 | 3 | 9 | 0 | 0.230 |
| 163 | Tidal Reverie | 5 | 2 | 6 | 0 | 0.229 |
| 164 | Jade Thompson | 3 | 3 | 8 | 0 | 0.224 |
| 165 | Lila "Lilly" Hartman | 3 | 3 | 8 | 0 | 0.224 |
| 166 | Ping Peng | 2 | 2 | 12 | 2 | 0.221 |
| 167 | Ethan Sanchez | 1 | 1 | 21 | 3 | 0.220 |
| 168 | Fang Gu | 1 | 1 | 21 | 3 | 0.220 |
| 169 | Ping Cui | 1 | 1 | 21 | 3 | 0.220 |
| 170 | Xiuying Yin | 1 | 1 | 21 | 3 | 0.220 |
| 171 | Yan Fang | 1 | 1 | 21 | 3 | 0.220 |
| 172 | Yan Liang | 1 | 1 | 21 | 3 | 0.220 |
| 173 | Selkie's Hollow | 5 | 2 | 4 | 0 | 0.219 |
| 174 | Wei Qian | 2 | 2 | 11 | 2 | 0.215 |
| 175 | Chao Tang | 1 | 1 | 20 | 3 | 0.215 |
| 176 | Gang Yin | 1 | 1 | 20 | 3 | 0.215 |
| 177 | Gang Zhang | 1 | 1 | 20 | 3 | 0.215 |
| 178 | Guiying Ding | 1 | 1 | 20 | 3 | 0.215 |
| 179 | Li Zou | 1 | 1 | 20 | 3 | 0.215 |
| 180 | Na Zou | 1 | 1 | 20 | 3 | 0.215 |
| 181 | Wei Chang | 1 | 1 | 20 | 3 | 0.215 |
| 182 | Xiuying Du | 1 | 1 | 20 | 3 | 0.215 |
| 183 | Arlo Sterling | 3 | 3 | 6 | 0 | 0.214 |
| 184 | Cassian Rae | 3 | 3 | 6 | 0 | 0.214 |
| 185 | Elara May | 3 | 3 | 6 | 0 | 0.214 |
| 186 | Lyra Blaze | 3 | 3 | 6 | 0 | 0.214 |
| 187 | Orion Cruz | 3 | 3 | 6 | 0 | 0.214 |
| 188 | Yan Zhou | 2 | 2 | 15 | 1 | 0.214 |
| 189 | Coriolano Luria-Scialpi | 1 | 1 | 15 | 4 | 0.212 |
| 190 | Arnaude Poirier | 1 | 1 | 19 | 3 | 0.210 |
| 191 | Christophe-Émile Grégoire | 1 | 1 | 19 | 3 | 0.210 |
| 192 | Georges Chrétien | 1 | 1 | 19 | 3 | 0.210 |
| 193 | Interval Shift | 1 | 1 | 19 | 3 | 0.210 |
| 194 | Luce Loiseau | 1 | 1 | 19 | 3 | 0.210 |
| 195 | Martino Michelangeli | 1 | 1 | 19 | 3 | 0.210 |
| 196 | Caleb Foster | 3 | 3 | 5 | 0 | 0.208 |
| 197 | Eleanor Wren | 3 | 3 | 5 | 0 | 0.208 |
| 198 | Kai Reynolds | 3 | 3 | 5 | 0 | 0.208 |
| 199 | Jie Xu | 2 | 2 | 13 | 1 | 0.203 |
| 200 | Na Dai | 2 | 2 | 13 | 1 | 0.203 |
| 201 | Xia Wu | 2 | 2 | 13 | 1 | 0.203 |
| 202 | Christine Ward | 1 | 1 | 17 | 3 | 0.199 |
| 203 | Donald Medina | 1 | 1 | 17 | 3 | 0.199 |
| 204 | Erik Mathews | 1 | 1 | 17 | 3 | 0.199 |
| 205 | Gang Shao | 1 | 1 | 17 | 3 | 0.199 |
| 206 | Jie Fan | 1 | 1 | 17 | 3 | 0.199 |
| 207 | Joshua Orozco | 1 | 1 | 17 | 3 | 0.199 |
| 208 | Jun Pan | 1 | 1 | 17 | 3 | 0.199 |
| 209 | Lisa Hofmann | 1 | 1 | 17 | 3 | 0.199 |
| 210 | Min Liang | 1 | 1 | 17 | 3 | 0.199 |
| 211 | Na Li | 1 | 1 | 17 | 3 | 0.199 |
| 212 | Na Yi | 1 | 1 | 17 | 3 | 0.199 |
| 213 | Sonora Flux | 1 | 1 | 17 | 3 | 0.199 |
| 214 | Steven Goodman | 1 | 1 | 17 | 3 | 0.199 |
| 215 | Wei Liao | 1 | 1 | 17 | 3 | 0.199 |
| 216 | Xia Shao | 1 | 1 | 17 | 3 | 0.199 |
| 217 | Xia Wang | 1 | 1 | 17 | 3 | 0.199 |
| 218 | Xiulan Lin | 1 | 1 | 17 | 3 | 0.199 |
| 219 | Yang Wu | 1 | 1 | 17 | 3 | 0.199 |
| 220 | The Wave Riders | 4 | 2 | 5 | 0 | 0.195 |
| 221 | Michael Reyes | 2 | 2 | 7 | 2 | 0.194 |
| 222 | Michael Rivera | 2 | 2 | 7 | 2 | 0.194 |
| 223 | Eric Hopkins | 1 | 1 | 16 | 3 | 0.194 |
| 224 | Guiying Tao | 1 | 1 | 16 | 3 | 0.194 |
| 225 | Min Bai | 1 | 1 | 16 | 3 | 0.194 |
| 226 | Ming Qiao | 1 | 1 | 16 | 3 | 0.194 |
| 227 | Ryan Mcguire | 1 | 1 | 16 | 3 | 0.194 |
| 228 | Stephen Allen | 1 | 1 | 16 | 3 | 0.194 |
| 229 | Yang Dai | 1 | 1 | 16 | 3 | 0.194 |
| 230 | Jun Yuan | 2 | 2 | 11 | 1 | 0.193 |
| 231 | Jing Xu | 1 | 1 | 15 | 3 | 0.189 |
| 232 | Juan Wen | 1 | 1 | 15 | 3 | 0.189 |
| 233 | Min Xue | 1 | 1 | 15 | 3 | 0.189 |
| 234 | Min Yu | 1 | 1 | 15 | 3 | 0.189 |
| 235 | Loro | 2 | 2 | 10 | 1 | 0.187 |
| 236 | Xiulan Yi | 2 | 2 | 10 | 1 | 0.187 |
| 237 | Siren's Call | 4 | 2 | 3 | 0 | 0.185 |
| 238 | Xiulan Dong | 2 | 2 | 9 | 1 | 0.182 |
| 239 | Yong Tang | 2 | 2 | 9 | 1 | 0.182 |
| 240 | Mariner's Refrain | 4 | 1 | 6 | 1 | 0.182 |
| 241 | Rüdiger Graf | 2 | 1 | 12 | 2 | 0.179 |
| 242 | Na Zhong | 2 | 2 | 8 | 1 | 0.177 |
| 243 | Evelyn Gordon | 1 | 1 | 17 | 2 | 0.177 |
| 244 | Gang Wang | 1 | 1 | 17 | 2 | 0.177 |
| 245 | Jie Yan | 1 | 1 | 17 | 2 | 0.177 |
| 246 | Min Gao | 1 | 1 | 17 | 2 | 0.177 |
| 247 | Richard Frazier | 1 | 1 | 17 | 2 | 0.177 |
| 248 | Sonia Weeks | 1 | 1 | 17 | 2 | 0.177 |
| 249 | Wei Cheng | 1 | 1 | 17 | 2 | 0.177 |
| 250 | Yan Hou | 1 | 1 | 17 | 2 | 0.177 |
| 251 | Lei Tao | 1 | 0 | 24 | 2 | 0.172 |
| 252 | Ming Song | 1 | 0 | 24 | 2 | 0.172 |
| 253 | Nadia van Dooren-de Jode Vastraedsd | 1 | 0 | 24 | 2 | 0.172 |
| 254 | Tao Zhao | 1 | 0 | 24 | 2 | 0.172 |
| 255 | Eric Bartlett | 1 | 1 | 16 | 2 | 0.171 |
| 256 | Min Yan | 1 | 1 | 16 | 2 | 0.171 |
| 257 | Xia Zeng | 1 | 1 | 16 | 2 | 0.171 |
| 258 | Yong Tao | 2 | 2 | 11 | 0 | 0.170 |
| 259 | Joker's Smile | 1 | 1 | 7 | 4 | 0.169 |
| 260 | Genevieve Bell | 4 | 2 | 0 | 0 | 0.169 |
| 261 | Chao Zeng | 1 | 1 | 11 | 3 | 0.168 |
| 262 | Gang Jiang | 1 | 1 | 11 | 3 | 0.168 |
| 263 | Xia Xiang | 1 | 1 | 11 | 3 | 0.168 |
| 264 | Guiying Ma | 1 | 1 | 15 | 2 | 0.166 |
| 265 | Jie Wu | 1 | 1 | 15 | 2 | 0.166 |
| 266 | Jing Li | 1 | 1 | 15 | 2 | 0.166 |
| 267 | Na Qian | 1 | 1 | 15 | 2 | 0.166 |
| 268 | Yong Wen | 1 | 1 | 15 | 2 | 0.166 |
| 269 | Jun Yi | 1 | 1 | 14 | 2 | 0.161 |
| 270 | Xia Yu | 1 | 1 | 14 | 2 | 0.161 |
| 271 | Min Huang | 2 | 2 | 9 | 0 | 0.159 |
| 272 | Yang Ma | 2 | 2 | 9 | 0 | 0.159 |
| 273 | David Nash | 1 | 1 | 13 | 2 | 0.156 |
| 274 | Fang Duan | 1 | 1 | 13 | 2 | 0.156 |
| 275 | Gang Yang | 1 | 1 | 13 | 2 | 0.156 |
| 276 | Jessica Beck | 1 | 1 | 13 | 2 | 0.156 |
| 277 | Kaori Kobayashi | 1 | 1 | 13 | 2 | 0.156 |
| 278 | Wei Lai | 1 | 1 | 13 | 2 | 0.156 |
| 279 | Xia Liu | 1 | 1 | 13 | 2 | 0.156 |
| 280 | Yong Dai | 1 | 1 | 13 | 2 | 0.156 |
| 281 | Yui Kondo | 1 | 1 | 13 | 2 | 0.156 |
| 282 | Juan Wu | 2 | 2 | 8 | 0 | 0.154 |
| 283 | Rusty Riggins | 2 | 2 | 8 | 0 | 0.154 |
| 284 | Ella Parker | 3 | 1 | 6 | 1 | 0.153 |
| 285 | Guiying Cao | 1 | 1 | 12 | 2 | 0.150 |
| 286 | Jing Kang | 1 | 1 | 12 | 2 | 0.150 |
| 287 | Luciano Chindamo | 1 | 1 | 12 | 2 | 0.150 |
| 288 | Silver Seraph | 1 | 1 | 12 | 2 | 0.150 |
| 289 | Chao Qiu | 2 | 2 | 7 | 0 | 0.149 |
| 290 | Yoko Fujita | 2 | 2 | 7 | 0 | 0.149 |
| 291 | Chao Zhou | 1 | 1 | 11 | 2 | 0.145 |
| 292 | Fenna Zwart | 1 | 1 | 11 | 2 | 0.145 |
| 293 | Kevin Ruiz | 1 | 1 | 11 | 2 | 0.145 |
| 294 | Kimberly Stanton | 1 | 1 | 11 | 2 | 0.145 |
| 295 | Lei Wei | 1 | 1 | 11 | 2 | 0.145 |
| 296 | Michael Anderson | 1 | 1 | 11 | 2 | 0.145 |
| 297 | Xiulan Gu | 1 | 1 | 11 | 2 | 0.145 |
| 298 | Ethan Clarke | 2 | 2 | 6 | 0 | 0.143 |
| 299 | Kara Lee | 2 | 2 | 6 | 0 | 0.143 |
| 300 | Michael Harris | 2 | 2 | 6 | 0 | 0.143 |
| 301 | Sophie Bennett | 2 | 2 | 6 | 0 | 0.143 |
| 302 | Tao Cui | 2 | 2 | 6 | 0 | 0.143 |
| 303 | Jose Garrett | 1 | 1 | 10 | 2 | 0.140 |
| 304 | Juan Pan | 1 | 1 | 10 | 2 | 0.140 |
| 305 | Juan Zeng | 1 | 1 | 10 | 2 | 0.140 |
| 306 | Lupe Miró | 1 | 1 | 10 | 2 | 0.140 |
| 307 | Ming Wan | 1 | 1 | 10 | 2 | 0.140 |
| 308 | Paulo Oestrovsky | 1 | 1 | 10 | 2 | 0.140 |
| 309 | Qiang He | 1 | 1 | 10 | 2 | 0.140 |
| 310 | Qiang Lai | 1 | 1 | 10 | 2 | 0.140 |
| 311 | Qiang Zhu | 1 | 1 | 10 | 2 | 0.140 |
| 312 | Aiden Harper | 2 | 2 | 5 | 0 | 0.138 |
| 313 | Finn Morgan | 2 | 2 | 5 | 0 | 0.138 |
| 314 | Skylar Brooks | 2 | 2 | 5 | 0 | 0.138 |
| 315 | Christine Turner | 1 | 1 | 9 | 2 | 0.134 |
| 316 | Gang Zeng | 1 | 1 | 9 | 2 | 0.134 |
| 317 | Li Dai | 1 | 1 | 9 | 2 | 0.134 |
| 318 | Min Ding | 1 | 1 | 9 | 2 | 0.134 |
| 319 | Nicholas Porter | 1 | 1 | 9 | 2 | 0.134 |
| 320 | Victoria Higgins | 1 | 1 | 9 | 2 | 0.134 |
| 321 | Xiuying Jia | 1 | 1 | 9 | 2 | 0.134 |
| 322 | Jing Guo | 1 | 1 | 13 | 1 | 0.133 |
| 323 | Li Wan | 1 | 1 | 13 | 1 | 0.133 |
| 324 | Mandy Hood | 1 | 1 | 13 | 1 | 0.133 |
| 325 | Min Kong | 1 | 1 | 13 | 1 | 0.133 |
| 326 | Operatic Pulse | 1 | 1 | 13 | 1 | 0.133 |
| 327 | Robert Villanueva | 1 | 1 | 13 | 1 | 0.133 |
| 328 | Yang Zhao | 1 | 1 | 13 | 1 | 0.133 |
| 329 | Carlos Duffy | 2 | 2 | 3 | 0 | 0.128 |
| 330 | Ewan MacCrae | 2 | 2 | 3 | 0 | 0.128 |
| 331 | Freya Lindholm | 2 | 2 | 3 | 0 | 0.128 |
| 332 | Justin Berry | 2 | 2 | 3 | 0 | 0.128 |
| 333 | Lila Rivers | 2 | 2 | 3 | 0 | 0.128 |
| 334 | Mia Waters | 2 | 2 | 3 | 0 | 0.128 |
| 335 | Mikayla Cook | 2 | 2 | 3 | 0 | 0.128 |
| 336 | Min Qin | 2 | 2 | 3 | 0 | 0.128 |
| 337 | Ming Du | 1 | 1 | 12 | 1 | 0.128 |
| 338 | Morgan Hernandez | 1 | 1 | 12 | 1 | 0.128 |
| 339 | Patricia Pope | 1 | 1 | 12 | 1 | 0.128 |
| 340 | Ping Shao | 1 | 1 | 12 | 1 | 0.128 |
| 341 | Yang Liang | 1 | 1 | 12 | 1 | 0.128 |
| 342 | Gang Fu | 1 | 1 | 6 | 2 | 0.119 |
| 343 | Li Long | 1 | 1 | 6 | 2 | 0.119 |
| 344 | Ping Zeng | 1 | 1 | 6 | 2 | 0.119 |
| 345 | Chao Fang | 1 | 1 | 10 | 1 | 0.117 |
| 346 | Gang Ding | 1 | 1 | 10 | 1 | 0.117 |
| 347 | Guiying Jin | 1 | 1 | 10 | 1 | 0.117 |
| 348 | Min Lei | 1 | 1 | 10 | 1 | 0.117 |
| 349 | Nicholas Moss | 1 | 1 | 10 | 1 | 0.117 |
| 350 | Qiang Jiang | 1 | 1 | 10 | 1 | 0.117 |
| 351 | Rachel Rios | 1 | 1 | 10 | 1 | 0.117 |
| 352 | Tammie Johnson | 1 | 1 | 10 | 1 | 0.117 |
| 353 | Xia Shen | 1 | 1 | 10 | 1 | 0.117 |
| 354 | Xiulan Zhou | 1 | 1 | 10 | 1 | 0.117 |
| 355 | Yan Chang | 1 | 1 | 10 | 1 | 0.117 |
| 356 | Yang Zhang | 1 | 1 | 10 | 1 | 0.117 |
| 357 | Beppe Agazzi-Muratori | 1 | 1 | 9 | 1 | 0.112 |
| 358 | Chao Jin | 1 | 1 | 9 | 1 | 0.112 |
| 359 | Chiyo Suzuki | 1 | 1 | 9 | 1 | 0.112 |
| 360 | Elena Nibali | 1 | 1 | 9 | 1 | 0.112 |
| 361 | Gang Bai | 1 | 1 | 9 | 1 | 0.112 |
| 362 | Jeffery Bailey | 1 | 1 | 9 | 1 | 0.112 |
| 363 | Jing Wei | 1 | 1 | 9 | 1 | 0.112 |
| 364 | Kana Mori | 1 | 1 | 9 | 1 | 0.112 |
| 365 | Kaori Watanabe | 1 | 1 | 9 | 1 | 0.112 |
| 366 | Karen Robinson | 1 | 1 | 9 | 1 | 0.112 |
| 367 | Li Yang | 1 | 1 | 9 | 1 | 0.112 |
| 368 | Min Zheng | 1 | 1 | 9 | 1 | 0.112 |
| 369 | Ming Wang | 1 | 1 | 9 | 1 | 0.112 |
| 370 | Ming Xiang | 1 | 1 | 9 | 1 | 0.112 |
| 371 | Ming Yan | 1 | 1 | 9 | 1 | 0.112 |
| 372 | Na Deng | 1 | 1 | 9 | 1 | 0.112 |
| 373 | Renata Manolesso | 1 | 1 | 9 | 1 | 0.112 |
| 374 | Taichi Sasaki | 1 | 1 | 9 | 1 | 0.112 |
| 375 | Tao Hu | 1 | 1 | 9 | 1 | 0.112 |
| 376 | Tao Zhang | 1 | 1 | 9 | 1 | 0.112 |
| 377 | Tomoya Nakamura | 1 | 1 | 9 | 1 | 0.112 |
| 378 | Tomoya Takahashi | 1 | 1 | 9 | 1 | 0.112 |
| 379 | Wei Chen | 1 | 1 | 9 | 1 | 0.112 |
| 380 | Xiulan Wang | 1 | 1 | 9 | 1 | 0.112 |
| 381 | Xiuying Kang | 1 | 1 | 9 | 1 | 0.112 |
| 382 | Yan Luo | 1 | 1 | 9 | 1 | 0.112 |
| 383 | Yuki Hashimoto | 1 | 1 | 9 | 1 | 0.112 |
| 384 | Zaira Balotelli-Peano | 1 | 1 | 9 | 1 | 0.112 |
| 385 | Eduardo Gonzalez | 1 | 1 | 8 | 1 | 0.106 |
| 386 | Guiying Qin | 1 | 1 | 8 | 1 | 0.106 |
| 387 | Justin Morse | 1 | 1 | 8 | 1 | 0.106 |
| 388 | Li He | 1 | 1 | 8 | 1 | 0.106 |
| 389 | Na Jin | 1 | 1 | 8 | 1 | 0.106 |
| 390 | Theresa Rivera | 1 | 1 | 8 | 1 | 0.106 |
| 391 | William Lynch | 1 | 1 | 8 | 1 | 0.106 |
| 392 | Amanda Ramos | 1 | 1 | 7 | 1 | 0.101 |
| 393 | Deborah Davis | 1 | 1 | 7 | 1 | 0.101 |
| 394 | Jie Chang | 1 | 1 | 7 | 1 | 0.101 |
| 395 | Jie Wan | 1 | 1 | 7 | 1 | 0.101 |
| 396 | Jie Wang | 1 | 1 | 7 | 1 | 0.101 |
| 397 | Kent Chen | 1 | 1 | 7 | 1 | 0.101 |
| 398 | Lei Jia | 1 | 1 | 7 | 1 | 0.101 |
| 399 | Li Gu | 1 | 1 | 7 | 1 | 0.101 |
| 400 | Min Liao | 1 | 1 | 7 | 1 | 0.101 |
| 401 | Min Zou | 1 | 1 | 7 | 1 | 0.101 |
| 402 | Regina Davis | 1 | 1 | 7 | 1 | 0.101 |
| 403 | Russell Bates | 1 | 1 | 7 | 1 | 0.101 |
| 404 | Tao Qian | 1 | 1 | 7 | 1 | 0.101 |
| 405 | Tao Su | 1 | 1 | 7 | 1 | 0.101 |
| 406 | Teresa Rivera | 1 | 1 | 7 | 1 | 0.101 |
| 407 | Whitney Humphrey | 1 | 1 | 7 | 1 | 0.101 |
| 408 | Xia Du | 1 | 1 | 7 | 1 | 0.101 |
| 409 | Xiuying Deng | 1 | 1 | 7 | 1 | 0.101 |
| 410 | Xiuying Fan | 1 | 1 | 7 | 1 | 0.101 |
| 411 | Xiuying Zhang | 1 | 1 | 7 | 1 | 0.101 |
| 412 | Yang Wan | 1 | 1 | 7 | 1 | 0.101 |
| 413 | Alexej Klotz | 1 | 1 | 6 | 1 | 0.096 |
| 414 | Autumn Walker | 1 | 1 | 6 | 1 | 0.096 |
| 415 | Christopher Smith | 1 | 1 | 6 | 1 | 0.096 |
| 416 | Elsbeth Löwer | 1 | 1 | 6 | 1 | 0.096 |
| 417 | Gang Meng | 1 | 1 | 6 | 1 | 0.096 |
| 418 | Guiying Pan | 1 | 1 | 6 | 1 | 0.096 |
| 419 | Jing Ding | 1 | 1 | 6 | 1 | 0.096 |
| 420 | Jing Zhang | 1 | 1 | 6 | 1 | 0.096 |
| 421 | Lagan Bhalla | 1 | 1 | 6 | 1 | 0.096 |
| 422 | Leif Bien | 1 | 1 | 6 | 1 | 0.096 |
| 423 | Li Xie | 1 | 1 | 6 | 1 | 0.096 |
| 424 | Li Zeng | 1 | 1 | 6 | 1 | 0.096 |
| 425 | Margaretha Sager | 1 | 1 | 6 | 1 | 0.096 |
| 426 | Nakul Samra | 1 | 1 | 6 | 1 | 0.096 |
| 427 | Ping Zheng | 1 | 1 | 6 | 1 | 0.096 |
| 428 | Timothy Hansen | 1 | 1 | 6 | 1 | 0.096 |
| 429 | Xia Zhu | 1 | 1 | 6 | 1 | 0.096 |
| 430 | Xiuying Duan | 1 | 1 | 6 | 1 | 0.096 |
| 431 | Jing Luo | 1 | 1 | 5 | 1 | 0.091 |
| 432 | Lei Qiu | 1 | 1 | 5 | 1 | 0.091 |
| 433 | Matthew Murphy | 1 | 1 | 5 | 1 | 0.091 |
| 434 | Qiang Cui | 1 | 1 | 5 | 1 | 0.091 |
| 435 | Xiulan Zhong | 1 | 1 | 5 | 1 | 0.091 |
| 436 | Ann Anderson | 1 | 1 | 4 | 1 | 0.085 |
| 437 | Min Mo | 1 | 1 | 4 | 1 | 0.085 |
| 438 | Ming Zhong | 1 | 1 | 4 | 1 | 0.085 |
| 439 | Ping Liao | 1 | 1 | 4 | 1 | 0.085 |
| 440 | Xiuying Mo | 1 | 1 | 4 | 1 | 0.085 |
| 441 | Finn McGraw | 1 | 1 | 8 | 0 | 0.084 |
| 442 | William Tidewell | 1 | 1 | 8 | 0 | 0.084 |
| 443 | Fang Yan | 1 | 1 | 7 | 0 | 0.079 |
| 444 | Jie Dong | 1 | 1 | 7 | 0 | 0.079 |
| 445 | Jie Long | 1 | 1 | 7 | 0 | 0.079 |
| 446 | Jing Chang | 1 | 1 | 7 | 0 | 0.079 |
| 447 | Juan Cao | 1 | 1 | 7 | 0 | 0.079 |
| 448 | Juan Xiang | 1 | 1 | 7 | 0 | 0.079 |
| 449 | Jun Lai | 1 | 1 | 7 | 0 | 0.079 |
| 450 | Li Dong | 1 | 1 | 7 | 0 | 0.079 |
| 451 | Min Guo | 1 | 1 | 7 | 0 | 0.079 |
| 452 | Qiang Gao | 1 | 1 | 7 | 0 | 0.079 |
| 453 | Qiang Sun | 1 | 1 | 7 | 0 | 0.079 |
| 454 | Tao Xu | 1 | 1 | 7 | 0 | 0.079 |
| 455 | Wei Yao | 1 | 1 | 7 | 0 | 0.079 |
| 456 | Yong Qiao | 1 | 1 | 7 | 0 | 0.079 |
| 457 | Leo Hamilton | 2 | 0 | 5 | 1 | 0.078 |
| 458 | Noah Bennett | 2 | 0 | 5 | 1 | 0.078 |
| 459 | Min Song | 1 | 1 | 2 | 1 | 0.075 |
| 460 | Yong Xia | 1 | 1 | 2 | 1 | 0.075 |
| 461 | Christopher Lowery | 1 | 1 | 6 | 0 | 0.073 |
| 462 | Ela Batra | 1 | 1 | 6 | 0 | 0.073 |
| 463 | Guiying Dong | 1 | 1 | 6 | 0 | 0.073 |
| 464 | Guiying Tang | 1 | 1 | 6 | 0 | 0.073 |
| 465 | Guiying Xia | 1 | 1 | 6 | 0 | 0.073 |
| 466 | Guiying Zhong | 1 | 1 | 6 | 0 | 0.073 |
| 467 | Jun Qiao | 1 | 1 | 6 | 0 | 0.073 |
| 468 | Jun Shao | 1 | 1 | 6 | 0 | 0.073 |
| 469 | Kimaya Srinivasan | 1 | 1 | 6 | 0 | 0.073 |
| 470 | Lei Liao | 1 | 1 | 6 | 0 | 0.073 |
| 471 | Lei Qian | 1 | 1 | 6 | 0 | 0.073 |
| 472 | Li Ding | 1 | 1 | 6 | 0 | 0.073 |
| 473 | Melissa Wheeler | 1 | 1 | 6 | 0 | 0.073 |
| 474 | Ming Yao | 1 | 1 | 6 | 0 | 0.073 |
| 475 | Na Cai | 1 | 1 | 6 | 0 | 0.073 |
| 476 | Na Guo | 1 | 1 | 6 | 0 | 0.073 |
| 477 | Na Jiang | 1 | 1 | 6 | 0 | 0.073 |
| 478 | Onkar Kata | 1 | 1 | 6 | 0 | 0.073 |
| 479 | Qiang Du | 1 | 1 | 6 | 0 | 0.073 |
| 480 | Qiang Yang | 1 | 1 | 6 | 0 | 0.073 |
| 481 | Ryan Devan | 1 | 1 | 6 | 0 | 0.073 |
| 482 | Tami Cox | 1 | 1 | 6 | 0 | 0.073 |
| 483 | Tao Long | 1 | 1 | 6 | 0 | 0.073 |
| 484 | Tara Kota | 1 | 1 | 6 | 0 | 0.073 |
| 485 | Thomas Ball | 1 | 1 | 6 | 0 | 0.073 |
| 486 | Tiya Sani | 1 | 1 | 6 | 0 | 0.073 |
| 487 | Wei Bai | 1 | 1 | 6 | 0 | 0.073 |
| 488 | Xia Kang | 1 | 1 | 6 | 0 | 0.073 |
| 489 | Yuvraj Dar | 1 | 1 | 6 | 0 | 0.073 |
| 490 | Amber Smith | 1 | 1 | 5 | 0 | 0.068 |
| 491 | Cardboard Twenty-Five | 1 | 1 | 5 | 0 | 0.068 |
| 492 | Chao Kang | 1 | 1 | 5 | 0 | 0.068 |
| 493 | Chao Wan | 1 | 1 | 5 | 0 | 0.068 |
| 494 | Chao Zheng | 1 | 1 | 5 | 0 | 0.068 |
| 495 | Cosmic Drift | 1 | 1 | 5 | 0 | 0.068 |
| 496 | Crimson Theorem | 1 | 1 | 5 | 0 | 0.068 |
| 497 | Daria Ceravolo | 1 | 1 | 5 | 0 | 0.068 |
| 498 | Fang Han | 1 | 1 | 5 | 0 | 0.068 |
| 499 | Fang Qiao | 1 | 1 | 5 | 0 | 0.068 |
| 500 | Fang Zhong | 1 | 1 | 5 | 0 | 0.068 |
| 501 | Fiesta Nocturna | 1 | 1 | 5 | 0 | 0.068 |
| 502 | Gang Fan | 1 | 1 | 5 | 0 | 0.068 |
| 503 | Guiying Qiu | 1 | 1 | 5 | 0 | 0.068 |
| 504 | Guiying Ye | 1 | 1 | 5 | 0 | 0.068 |
| 505 | Jie Bai | 1 | 1 | 5 | 0 | 0.068 |
| 506 | Jie Su | 1 | 1 | 5 | 0 | 0.068 |
| 507 | Jing Cui | 1 | 1 | 5 | 0 | 0.068 |
| 508 | Joseph Cole | 1 | 1 | 5 | 0 | 0.068 |
| 509 | Jun Fu | 1 | 1 | 5 | 0 | 0.068 |
| 510 | Jun Ren | 1 | 1 | 5 | 0 | 0.068 |
| 511 | Jun Wen | 1 | 1 | 5 | 0 | 0.068 |
| 512 | Li Li | 1 | 1 | 5 | 0 | 0.068 |
| 513 | Li Qiao | 1 | 1 | 5 | 0 | 0.068 |
| 514 | Lisa Pennington | 1 | 1 | 5 | 0 | 0.068 |
| 515 | Liwia Piejko | 1 | 1 | 5 | 0 | 0.068 |
| 516 | Min Tian | 1 | 1 | 5 | 0 | 0.068 |
| 517 | Min Xiong | 1 | 1 | 5 | 0 | 0.068 |
| 518 | Ming Qiu | 1 | 1 | 5 | 0 | 0.068 |
| 519 | Na Han | 1 | 1 | 5 | 0 | 0.068 |
| 520 | Nicole Thomas | 1 | 1 | 5 | 0 | 0.068 |
| 521 | Ping Meng | 1 | 1 | 5 | 0 | 0.068 |
| 522 | Ping Tao | 1 | 1 | 5 | 0 | 0.068 |
| 523 | Rachel Ford | 1 | 1 | 5 | 0 | 0.068 |
| 524 | Ryan Adams | 1 | 1 | 5 | 0 | 0.068 |
| 525 | Stella Fusani | 1 | 1 | 5 | 0 | 0.068 |
| 526 | Tao Xiong | 1 | 1 | 5 | 0 | 0.068 |
| 527 | Tao Yin | 1 | 1 | 5 | 0 | 0.068 |
| 528 | Xiuying Shao | 1 | 1 | 5 | 0 | 0.068 |
| 529 | Yan Huang | 1 | 1 | 5 | 0 | 0.068 |
| 530 | Yang Lei | 1 | 1 | 5 | 0 | 0.068 |
| 531 | Yong Wang | 1 | 1 | 5 | 0 | 0.068 |
| 532 | Jennifer Alexander | 1 | 0 | 8 | 1 | 0.065 |
| 533 | Lauren Steele | 1 | 0 | 8 | 1 | 0.065 |
| 534 | Lori Young | 1 | 0 | 8 | 1 | 0.065 |
| 535 | Sean Riggs | 1 | 0 | 8 | 1 | 0.065 |
| 536 | Abigail Hawkins | 1 | 1 | 4 | 0 | 0.063 |
| 537 | Amanda Coleman | 1 | 1 | 4 | 0 | 0.063 |
| 538 | Andrew Lee | 1 | 1 | 4 | 0 | 0.063 |
| 539 | Carly Luna | 1 | 1 | 4 | 0 | 0.063 |
| 540 | Chao Cheng | 1 | 1 | 4 | 0 | 0.063 |
| 541 | Chao Lu | 1 | 1 | 4 | 0 | 0.063 |
| 542 | Chao Sun | 1 | 1 | 4 | 0 | 0.063 |
| 543 | Charles Vazquez | 1 | 1 | 4 | 0 | 0.063 |
| 544 | Chelsea Harris | 1 | 1 | 4 | 0 | 0.063 |
| 545 | David Morgan | 1 | 1 | 4 | 0 | 0.063 |
| 546 | Devin Chan | 1 | 1 | 4 | 0 | 0.063 |
| 547 | Donna Ryan | 1 | 1 | 4 | 0 | 0.063 |
| 548 | Fang Luo | 1 | 1 | 4 | 0 | 0.063 |
| 549 | Fang Zhou | 1 | 1 | 4 | 0 | 0.063 |
| 550 | Frédéric de la Coulon | 1 | 1 | 4 | 0 | 0.063 |
| 551 | Gang Lai | 1 | 1 | 4 | 0 | 0.063 |
| 552 | Gang Tian | 1 | 1 | 4 | 0 | 0.063 |
| 553 | Gang Yuan | 1 | 1 | 4 | 0 | 0.063 |
| 554 | Guiying Fan | 1 | 1 | 4 | 0 | 0.063 |
| 555 | Guiying Yang | 1 | 1 | 4 | 0 | 0.063 |
| 556 | Jenna York | 1 | 1 | 4 | 0 | 0.063 |
| 557 | Jennifer Harris | 1 | 1 | 4 | 0 | 0.063 |
| 558 | Jie Zhong | 1 | 1 | 4 | 0 | 0.063 |
| 559 | Jing Xiang | 1 | 1 | 4 | 0 | 0.063 |
| 560 | Juan Chen | 1 | 1 | 4 | 0 | 0.063 |
| 561 | Juan Han | 1 | 1 | 4 | 0 | 0.063 |
| 562 | Juan Wang | 1 | 1 | 4 | 0 | 0.063 |
| 563 | Jörg Niemeier | 1 | 1 | 4 | 0 | 0.063 |
| 564 | Kimberly Moore | 1 | 1 | 4 | 0 | 0.063 |
| 565 | Kinship Harmony | 1 | 1 | 4 | 0 | 0.063 |
| 566 | Lei Peng | 1 | 1 | 4 | 0 | 0.063 |
| 567 | Lei Tang | 1 | 1 | 4 | 0 | 0.063 |
| 568 | Lei Xue | 1 | 1 | 4 | 0 | 0.063 |
| 569 | Li Bai | 1 | 1 | 4 | 0 | 0.063 |
| 570 | Li Deng | 1 | 1 | 4 | 0 | 0.063 |
| 571 | Lia Grant | 1 | 1 | 4 | 0 | 0.063 |
| 572 | Mary King | 1 | 1 | 4 | 0 | 0.063 |
| 573 | Mary Parsons | 1 | 1 | 4 | 0 | 0.063 |
| 574 | Maurice Harrison | 1 | 1 | 4 | 0 | 0.063 |
| 575 | Michael Gregory | 1 | 1 | 4 | 0 | 0.063 |
| 576 | Michael Jefferson | 1 | 1 | 4 | 0 | 0.063 |
| 577 | Michelle Weiss | 1 | 1 | 4 | 0 | 0.063 |
| 578 | Min Xia | 1 | 1 | 4 | 0 | 0.063 |
| 579 | Ming Liu | 1 | 1 | 4 | 0 | 0.063 |
| 580 | Mitchell Bryan | 1 | 1 | 4 | 0 | 0.063 |
| 581 | Paul-Louis Benard | 1 | 1 | 4 | 0 | 0.063 |
| 582 | Ping Chang | 1 | 1 | 4 | 0 | 0.063 |
| 583 | Ping Feng | 1 | 1 | 4 | 0 | 0.063 |
| 584 | Ping Wu | 1 | 1 | 4 | 0 | 0.063 |
| 585 | Ping Xu | 1 | 1 | 4 | 0 | 0.063 |
| 586 | Ricardo Ward | 1 | 1 | 4 | 0 | 0.063 |
| 587 | Scott Burke | 1 | 1 | 4 | 0 | 0.063 |
| 588 | Tao Du | 1 | 1 | 4 | 0 | 0.063 |
| 589 | Tao Zou | 1 | 1 | 4 | 0 | 0.063 |
| 590 | The Nulls | 1 | 1 | 4 | 0 | 0.063 |
| 591 | Valérie Mathieu | 1 | 1 | 4 | 0 | 0.063 |
| 592 | Victoria Vazquez | 1 | 1 | 4 | 0 | 0.063 |
| 593 | Xia Ye | 1 | 1 | 4 | 0 | 0.063 |
| 594 | Xia Zhao | 1 | 1 | 4 | 0 | 0.063 |
| 595 | Xiulan Hu | 1 | 1 | 4 | 0 | 0.063 |
| 596 | Xiulan Lu | 1 | 1 | 4 | 0 | 0.063 |
| 597 | Yan Yan | 1 | 1 | 4 | 0 | 0.063 |
| 598 | Yang Mo | 1 | 1 | 4 | 0 | 0.063 |
| 599 | Yang Shao | 1 | 1 | 4 | 0 | 0.063 |
| 600 | Yong Wu | 1 | 1 | 4 | 0 | 0.063 |
| 601 | Zachary Cole | 1 | 1 | 4 | 0 | 0.063 |
| 602 | Éric Lamy | 1 | 1 | 4 | 0 | 0.063 |
| 603 | Amber Ramsey | 1 | 1 | 3 | 0 | 0.057 |
| 604 | Amedeo Mimun | 1 | 1 | 3 | 0 | 0.057 |
| 605 | Angela Perez | 1 | 1 | 3 | 0 | 0.057 |
| 606 | Astrid Nørgaard | 1 | 1 | 3 | 0 | 0.057 |
| 607 | Chad Marks | 1 | 1 | 3 | 0 | 0.057 |
| 608 | Christine Brown | 1 | 1 | 3 | 0 | 0.057 |
| 609 | Christine Jones | 1 | 1 | 3 | 0 | 0.057 |
| 610 | Christopher Reilly | 1 | 1 | 3 | 0 | 0.057 |
| 611 | Daniel Oneill | 1 | 1 | 3 | 0 | 0.057 |
| 612 | Deborah Norton | 1 | 1 | 3 | 0 | 0.057 |
| 613 | Edward Little | 1 | 1 | 3 | 0 | 0.057 |
| 614 | Fang Xiang | 1 | 1 | 3 | 0 | 0.057 |
| 615 | Gang Shen | 1 | 1 | 3 | 0 | 0.057 |
| 616 | Ida Vigliotti | 1 | 1 | 3 | 0 | 0.057 |
| 617 | Jacob Arnold | 1 | 1 | 3 | 0 | 0.057 |
| 618 | Jeffrey Watson | 1 | 1 | 3 | 0 | 0.057 |
| 619 | Jie Cheng | 1 | 1 | 3 | 0 | 0.057 |
| 620 | Jimmy Arnold | 1 | 1 | 3 | 0 | 0.057 |
| 621 | Jing Xiao | 1 | 1 | 3 | 0 | 0.057 |
| 622 | Juan Cheng | 1 | 1 | 3 | 0 | 0.057 |
| 623 | Juan Deng | 1 | 1 | 3 | 0 | 0.057 |
| 624 | Juan Kang | 1 | 1 | 3 | 0 | 0.057 |
| 625 | Jun Hao | 1 | 1 | 3 | 0 | 0.057 |
| 626 | Jun Wang | 1 | 1 | 3 | 0 | 0.057 |
| 627 | Jun Ye | 1 | 1 | 3 | 0 | 0.057 |
| 628 | Jun Zou | 1 | 1 | 3 | 0 | 0.057 |
| 629 | Latasha Watts | 1 | 1 | 3 | 0 | 0.057 |
| 630 | Lei Su | 1 | 1 | 3 | 0 | 0.057 |
| 631 | Lei Zheng | 1 | 1 | 3 | 0 | 0.057 |
| 632 | Li Zhou | 1 | 1 | 3 | 0 | 0.057 |
| 633 | Margherita Giammusso | 1 | 1 | 3 | 0 | 0.057 |
| 634 | Monica Murphy | 1 | 1 | 3 | 0 | 0.057 |
| 635 | Pina Garrone | 1 | 1 | 3 | 0 | 0.057 |
| 636 | Ping Bai | 1 | 1 | 3 | 0 | 0.057 |
| 637 | Ping Song | 1 | 1 | 3 | 0 | 0.057 |
| 638 | Qiang Han | 1 | 1 | 3 | 0 | 0.057 |
| 639 | Qiang Mo | 1 | 1 | 3 | 0 | 0.057 |
| 640 | Susan Randall | 1 | 1 | 3 | 0 | 0.057 |
| 641 | Tao Shen | 1 | 1 | 3 | 0 | 0.057 |
| 642 | Xiulan Lai | 1 | 1 | 3 | 0 | 0.057 |
| 643 | Yan Wang | 1 | 1 | 3 | 0 | 0.057 |
| 644 | Yan Zhu | 1 | 1 | 3 | 0 | 0.057 |
| 645 | Yang Qian | 1 | 1 | 3 | 0 | 0.057 |
| 646 | Yong Feng | 1 | 1 | 3 | 0 | 0.057 |
| 647 | Andrew Carrillo | 1 | 1 | 2 | 0 | 0.052 |
| 648 | Chao Mo | 1 | 1 | 2 | 0 | 0.052 |
| 649 | Douglas Roberts | 1 | 1 | 2 | 0 | 0.052 |
| 650 | Fiona Mercer | 1 | 1 | 2 | 0 | 0.052 |
| 651 | Gang Lin | 1 | 1 | 2 | 0 | 0.052 |
| 652 | Gang Pan | 1 | 1 | 2 | 0 | 0.052 |
| 653 | Isaiah Morales | 1 | 1 | 2 | 0 | 0.052 |
| 654 | Jason Vaughn | 1 | 1 | 2 | 0 | 0.052 |
| 655 | Jill Smith | 1 | 1 | 2 | 0 | 0.052 |
| 656 | John Maldonado | 1 | 1 | 2 | 0 | 0.052 |
| 657 | Juan Gong | 1 | 1 | 2 | 0 | 0.052 |
| 658 | Jun Yu | 1 | 1 | 2 | 0 | 0.052 |
| 659 | Katelyn Johnson | 1 | 1 | 2 | 0 | 0.052 |
| 660 | Kyle Lawrence | 1 | 1 | 2 | 0 | 0.052 |
| 661 | Li Wen | 1 | 1 | 2 | 0 | 0.052 |
| 662 | Li Xiong | 1 | 1 | 2 | 0 | 0.052 |
| 663 | Liam O'Sullivan | 1 | 1 | 2 | 0 | 0.052 |
| 664 | Mary Morales | 1 | 1 | 2 | 0 | 0.052 |
| 665 | Michael Snyder | 1 | 1 | 2 | 0 | 0.052 |
| 666 | Michaela Brooks | 1 | 1 | 2 | 0 | 0.052 |
| 667 | Michelangelo Berlusconi | 1 | 1 | 2 | 0 | 0.052 |
| 668 | Ming Zhou | 1 | 1 | 2 | 0 | 0.052 |
| 669 | Miss Erin Dean | 1 | 1 | 2 | 0 | 0.052 |
| 670 | Na Lai | 1 | 1 | 2 | 0 | 0.052 |
| 671 | Nancy Arnold | 1 | 1 | 2 | 0 | 0.052 |
| 672 | Raymond Martin | 1 | 1 | 2 | 0 | 0.052 |
| 673 | Richard Mckenzie | 1 | 1 | 2 | 0 | 0.052 |
| 674 | Stephanie Benjamin | 1 | 1 | 2 | 0 | 0.052 |
| 675 | Stephen Meyer | 1 | 1 | 2 | 0 | 0.052 |
| 676 | Steven Williams | 1 | 1 | 2 | 0 | 0.052 |
| 677 | Summer Bender | 1 | 1 | 2 | 0 | 0.052 |
| 678 | Tao Kong | 1 | 1 | 2 | 0 | 0.052 |
| 679 | Wei Zou | 1 | 1 | 2 | 0 | 0.052 |
| 680 | Xia Yan | 1 | 1 | 2 | 0 | 0.052 |
| 681 | Xiulan Liang | 1 | 1 | 2 | 0 | 0.052 |
| 682 | Xiulan Zhang | 1 | 1 | 2 | 0 | 0.052 |
| 683 | Xiuying Xie | 1 | 1 | 2 | 0 | 0.052 |
| 684 | Yan Tao | 1 | 1 | 2 | 0 | 0.052 |
| 685 | Yang Zhong | 1 | 1 | 2 | 0 | 0.052 |
| 686 | Yong Ding | 1 | 1 | 2 | 0 | 0.052 |
| 687 | Yong Tan | 1 | 1 | 2 | 0 | 0.052 |
| 688 | Bronze Tiger | 1 | 0 | 5 | 1 | 0.049 |
| 689 | Dustin Maxwell | 1 | 1 | 1 | 0 | 0.047 |
| 690 | Erin Martinez | 1 | 1 | 1 | 0 | 0.047 |
| 691 | Ishaan Bal | 1 | 1 | 1 | 0 | 0.047 |
| 692 | Isla Quinn | 1 | 1 | 1 | 0 | 0.047 |
| 693 | Jessica Carney | 1 | 1 | 1 | 0 | 0.047 |
| 694 | Jun Bai | 1 | 1 | 1 | 0 | 0.047 |
| 695 | Lei Kong | 1 | 1 | 1 | 0 | 0.047 |
| 696 | Michael Smith | 1 | 1 | 1 | 0 | 0.047 |
| 697 | Ping Zhao | 1 | 1 | 1 | 0 | 0.047 |
| 698 | Riya Dhingra | 1 | 1 | 1 | 0 | 0.047 |
| 699 | Shlok Cherian | 1 | 1 | 1 | 0 | 0.047 |
| 700 | Tanya Garrett | 1 | 1 | 1 | 0 | 0.047 |
| 701 | Tara Deshmukh | 1 | 1 | 1 | 0 | 0.047 |
| 702 | William Knapp | 1 | 1 | 1 | 0 | 0.047 |
| 703 | Xiulan Hao | 1 | 1 | 1 | 0 | 0.047 |
| 704 | Xiuying Liang | 1 | 1 | 1 | 0 | 0.047 |
| 705 | Yang Gong | 1 | 1 | 1 | 0 | 0.047 |
| 706 | Jing Feng | 1 | 1 | 0 | 0 | 0.042 |
| 707 | Guiying Gong | 1 | 0 | 6 | 0 | 0.032 |
| 708 | Jing Jin | 1 | 0 | 6 | 0 | 0.032 |
| 709 | Ming Deng | 1 | 0 | 6 | 0 | 0.032 |
| 710 | Ming Jia | 1 | 0 | 6 | 0 | 0.032 |
| 711 | Tao Xue | 1 | 0 | 6 | 0 | 0.032 |
| 712 | Whispered Resonance | 1 | 0 | 6 | 0 | 0.032 |
| 713 | Xiuying Fang | 1 | 0 | 6 | 0 | 0.032 |
| 714 | Gang Xiong | 1 | 0 | 3 | 0 | 0.016 |
| 715 | Li Huang | 1 | 0 | 3 | 0 | 0.016 |
| 716 | Qiang Luo | 1 | 0 | 3 | 0 | 0.016 |
| 717 | Yong Ye | 1 | 0 | 3 | 0 | 0.016 |
| 718 | Jonathan Morris | 1 | 0 | 2 | 0 | 0.011 |
| 719 | Ming Xiao | 1 | 0 | 2 | 0 | 0.011 |
| 720 | Xiuying Wei | 1 | 0 | 2 | 0 | 0.011 |
6.3.2 Visualizing the career of Sailor Shift
Show Code
# Data Preparation
chosen_creator_1 = "Sailor Shift"
# Step 1: Get the node of the chosen creator
chosen_node_1 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1) %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the top creator produced
creator_songs_1 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
creators_songs_collaborate_influence_1 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1,
infuence_music_collaborate != chosen_node_1) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
creators_songs_influence_1 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1,
infuence_music_collaborate != chosen_node_1,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
creators_songs_influence_creators_1 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_1,
influence_creator != chosen_node_1,
!is.na(influence_creator),
infuence_music_collaborate %in% creators_songs_influence_1) %>%
pull(influence_creator)
all_nodes <- unique(c(chosen_node_1,
creator_songs_1,
creators_songs_collaborate_influence_1,
creators_songs_influence_creators_1))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == chosen_creator_1, 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == chosen_creator_1, chosen_creator_1, NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)Show Code
# Data Preparation
# Step 1: Count number of music by release date
music_by_date_1 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_1)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = music_by_date_1,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of notable music by release date
notable_music_by_date_1 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_1), notable == TRUE) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = notable_music_by_date_1,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Notable Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced artists by release date
influence_artists_by_date_1 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% unique(chosen_node_1),
influence_creator != unique(chosen_node_1)) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "music_count") %>%
arrange(first_influence_date) %>%
rename(creator_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_artists_by_date_1,
x = ~creator_release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_song_by_date_1 <- mc1_nodes_clean %>%
filter(name %in% unique(creators_songs_influence_1)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_song_by_date_1,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Music",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)6.3.3 Visualizing the career of Chao Wu
Show Code
# Data Preparation
chosen_creator_2 = "Chao Wu"
# Step 1: Get the node of the chosen creator
chosen_node_2 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2) %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the top creator produced
creator_songs_2 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
creators_songs_collaborate_influence_2 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2,
infuence_music_collaborate != chosen_node_2) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
creators_songs_influence_2 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2,
infuence_music_collaborate != chosen_node_2,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
creators_songs_influence_creators_2 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_2,
influence_creator != chosen_node_2,
!is.na(influence_creator),
infuence_music_collaborate %in% creators_songs_influence_2) %>%
pull(influence_creator)
all_nodes <- unique(c(chosen_node_2,
creator_songs_2,
creators_songs_collaborate_influence_2,
creators_songs_influence_creators_2))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == chosen_creator_2, 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == chosen_creator_2, chosen_creator_2, NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)Show Code
# Data Preparation
# Step 1: Count number of music by release date
music_by_date_2 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_2)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = music_by_date_2,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of notable music by release date
notable_music_by_date_2 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_2), notable == TRUE) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = notable_music_by_date_2,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Notable Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced artists by release date
influence_artists_by_date_2 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% unique(chosen_node_2),
influence_creator != unique(chosen_node_2)) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "music_count") %>%
arrange(first_influence_date) %>%
rename(creator_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_artists_by_date_2,
x = ~creator_release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_song_by_date_2 <- mc1_nodes_clean %>%
filter(name %in% unique(creators_songs_influence_2)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_song_by_date_2,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Music",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)6.3.4 Visualizing the career of Xia Jia
Show Code
# Data Preparation
chosen_creator_3 = "Xia Jia"
# Step 1: Get the node of the chosen creator
chosen_node_3 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3) %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the top creator produced
creator_songs_3 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
creators_songs_collaborate_influence_3 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3,
infuence_music_collaborate != chosen_node_3) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
creators_songs_influence_3 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3,
infuence_music_collaborate != chosen_node_3,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
creators_songs_influence_creators_3 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_3,
influence_creator != chosen_node_3,
!is.na(influence_creator),
infuence_music_collaborate %in% creators_songs_influence_3) %>%
pull(influence_creator)
all_nodes <- unique(c(chosen_node_3,
creator_songs_3,
creators_songs_collaborate_influence_3,
creators_songs_influence_creators_3))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == chosen_creator_3, 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == chosen_creator_3, chosen_creator_3, NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)Show Code
# Data Preparation
# Step 1: Count number of music by release date
music_by_date_3 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_3)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = music_by_date_3,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of notable music by release date
notable_music_by_date_3 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_3), notable == TRUE) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = notable_music_by_date_3,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Notable Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced artists by release date
influence_artists_by_date_3 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% unique(chosen_node_3),
influence_creator != unique(chosen_node_3)) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "music_count") %>%
arrange(first_influence_date) %>%
rename(creator_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_artists_by_date_3,
x = ~creator_release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_song_by_date_3 <- mc1_nodes_clean %>%
filter(name %in% unique(creators_songs_influence_3)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_song_by_date_3,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Music",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)6.3.5 Visualizing the career of Donna Caldwell
Show Code
# Data Preparation
chosen_creator_4 = "Donna Caldwell"
# Step 1: Get the node of the chosen creator
chosen_node_4 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_4) %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the top creator produced
creator_songs_4 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_4) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
creators_songs_collaborate_influence_4 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_4,
infuence_music_collaborate != chosen_node_4) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
creators_songs_influence_4 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_4,
infuence_music_collaborate != chosen_node_4,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
creators_songs_influence_creators_4 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_4,
influence_creator != chosen_node_4,
!is.na(influence_creator),
infuence_music_collaborate %in% creators_songs_influence_4) %>%
pull(influence_creator)
all_nodes <- unique(c(chosen_node_4,
creator_songs_4,
creators_songs_collaborate_influence_4,
creators_songs_influence_creators_4))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == chosen_creator_4, 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == chosen_creator_4, chosen_creator_4, NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)Show Code
# Data Preparation
# Step 1: Count number of music by release date
music_by_date_4 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_4)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = music_by_date_4,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of notable music by release date
notable_music_by_date_4 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_4), notable == TRUE) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = notable_music_by_date_4,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Notable Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced artists by release date
influence_artists_by_date_4 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% unique(chosen_node_4),
influence_creator != unique(chosen_node_4)) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "music_count") %>%
arrange(first_influence_date) %>%
rename(creator_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_artists_by_date_4,
x = ~creator_release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_song_by_date_4 <- mc1_nodes_clean %>%
filter(name %in% unique(creators_songs_influence_4)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_song_by_date_4,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Music",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)6.3.6 Visualizing the career of Xiulan Ye
Show Code
# Data Preparation
chosen_creator_5 = "Xiulan Ye"
# Step 1: Get the node of the chosen creator
chosen_node_5 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_5) %>%
pull(creator_from) %>%
unique()
# Step 2: Get the songs that the top creator produced
creator_songs_5 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_5) %>%
pull(song_to)
# Step 3: Get the songs they have influenced / artists they collaborate with
creators_songs_collaborate_influence_5 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_5,
infuence_music_collaborate != chosen_node_5) %>%
pull(infuence_music_collaborate)
# Step 4: Get the songs they have influenced
creators_songs_influence_5 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_5,
infuence_music_collaborate != chosen_node_5,
`Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate)
# Step 5: Get the influenced creators of the influenced songs
creators_songs_influence_creators_5 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == chosen_creator_5,
influence_creator != chosen_node_5,
!is.na(influence_creator),
infuence_music_collaborate %in% creators_songs_influence_5) %>%
pull(influence_creator)
all_nodes <- unique(c(chosen_node_5,
creator_songs_5,
creators_songs_collaborate_influence_5,
creators_songs_influence_creators_5))
# Create subgraph
sub_graph <- graph %>%
filter(name %in% all_nodes)
# Visualisation
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(node_name == chosen_creator_5, 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(node_name == chosen_creator_5, chosen_creator_5, NA)
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)Show Code
# Data Preparation
# Step 1: Count number of music by release date
music_by_date_5 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_5)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = music_by_date_5,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of notable music by release date
notable_music_by_date_5 <- mc1_nodes_clean %>%
filter(name %in% unique(creator_songs_5), notable == TRUE) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = notable_music_by_date_5,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Notable Music Releases",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Released Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced artists by release date
influence_artists_by_date_5 <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% unique(chosen_node_5),
influence_creator != unique(chosen_node_5)) %>%
# Get unique artist-date pairs first
distinct(influence_creator, influence_release_date) %>%
# Find first influence date for each artist
group_by(influence_creator) %>%
summarize(
first_influence_date = if(n() > 0) min(influence_release_date) else NA_real_,
.groups = "drop"
) %>%
# Count new artists by first influence date
count(first_influence_date, name = "music_count") %>%
arrange(first_influence_date) %>%
rename(creator_release_date = first_influence_date) %>%
# Calculate cumulative unique artists
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_artists_by_date_5,
x = ~creator_release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Artists",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)Show Code
# Data Preparation
# Step 1: Count number of influenced music by release date
influence_song_by_date_5 <- mc1_nodes_clean %>%
filter(name %in% unique(creators_songs_influence_5)) %>%
count(release_date, name = "music_count") %>%
arrange(release_date) %>% # Ensure dates are in chronological order
mutate(cumulative_count = cumsum(music_count))
# Visualisation
plot_ly(
data = influence_song_by_date_5,
x = ~release_date,
y = ~music_count,
type = "bar",
name = "Number of Influenced Music",
marker = list(color = "#2E3192"),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Count: ", music_count
)
) %>%
add_trace(
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = "Cumulative Count",
line = list(color = "black", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
)
)6.3.7 Compare and contrast the five artists’ rise in popularity and influence
The cumulative graphs of the 5 artists (Sailor Shift, Chao Wu, Xia Jia, Donna Caldwell, and Xiulan Ye) will be overlaid for comparison of their musical careers.
Show Code
# Visualisation
plot_ly(
data = music_by_date_1,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_1,
line = list(color = "#2E3192", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_1,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = music_by_date_2,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_2,
line = list(color = "green", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_2,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = music_by_date_3,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_3,
line = list(color = "purple", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_3,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = music_by_date_4,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_4,
line = list(color = "orange", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_4,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = music_by_date_5,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_5,
line = list(color = "skyblue", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_5,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
),
annotations = list(
list(
x = 2017,
y = 2,
text = "<b>2017:<br>Donna Caldwell <br>& Xiulan Ye</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -15,
font = list(color="black", size=12)
)
)
)
Note
Donna Caldwell and Xiulan Ye are at 2017 with a count of 2.
Show Code
# Visualisation
plot_ly(
data = notable_music_by_date_1,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_1,
line = list(color = "#2E3192", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_1,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = notable_music_by_date_2,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_2,
line = list(color = "green", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_2,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = notable_music_by_date_3,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_3,
line = list(color = "purple", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_3,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = notable_music_by_date_4,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_4,
line = list(color = "orange", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_4,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = notable_music_by_date_5,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_5,
line = list(color = "skyblue", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_5,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Notable Music (Song/Album) Releases",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
),
annotations = list(
list(
x = 2017,
y = 1,
text = "<b>2017:<br>Donna Caldwell <br>& Xiulan Ye</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -15,
font = list(color="black", size=12)
)
)
)
Note
Donna Caldwell and Xiulan Ye are at 2017 with a count of 1.
Show Code
# Visualisation
plot_ly(
data = influence_artists_by_date_1,
x = ~creator_release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_1,
line = list(color = "#2E3192", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_1,
"<br>Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_artists_by_date_2,
x = ~creator_release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_2,
line = list(color = "green", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_2,
"<br>Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_artists_by_date_3,
x = ~creator_release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_3,
line = list(color = "purple", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_3,
"<br>Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_artists_by_date_4,
x = ~creator_release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_4,
line = list(color = "orange", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_4,
"<br>Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_artists_by_date_5,
x = ~creator_release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_5,
line = list(color = "skyblue", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_5,
"<br>Influence Date: ", creator_release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Annual Count of New Artist Influences & Collaborations",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
),
annotations = list(
list(
x = 2029,
y = 159,
text = "<b>Donna Caldwell</b>",
xref = "x", yref = "y",
xanchor = "left",
showarrow = TRUE, arrowhead = 2,
ax = 30, ay = 30,
font = list(color="black", size=12)
)
)
)
Note
Donna Caldwell overlaps with Xiulan Ye
Show Code
# Visualisation
plot_ly(
data = influence_song_by_date_1,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_1,
line = list(color = "#2E3192", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_1,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_song_by_date_2,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_2,
line = list(color = "green", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_2,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_song_by_date_3,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_3,
line = list(color = "purple", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_3,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_song_by_date_4,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_4,
line = list(color = "orange", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_4,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
add_trace(
data = influence_song_by_date_5,
x = ~release_date,
y = ~cumulative_count,
type = "scatter",
mode = "lines+markers",
name = chosen_creator_5,
line = list(color = "skyblue", width = 2),
marker = list(color = "red", size = 6),
hoverinfo = "text",
hovertext = ~paste0(
"Artist: ", chosen_creator_5,
"<br>Influence Date: ", release_date,
"<br>Cumulative Count: ", cumulative_count
)
) %>%
layout(
title = "Yearly Music (Song/Album) Influence",
margin = list(b = 80, t = 80),
xaxis = list(
title = NA,
dtick = 5,
automargin = TRUE
),
yaxis = list(
title = "Count",
automargin = TRUE
),
legend = list(
orientation = "h",
x = 0.5,
xanchor = "center",
y = -0.1
),
annotations = list(
list(
x = 2024,
y = 16,
text = "<b>Donna Caldwell</b>",
xref = "x", yref = "y",
xanchor = "right",
showarrow = TRUE, arrowhead = 2,
ax = -30, ay = -20,
font = list(color="black", size=12)
)
)
)
Note
- Donna Caldwell overlaps with Xiulan Ye
- Sailor Shift has no influence
6.3.8 Analysing the relationships between these five artists
Show Code
# Data Preparation
# Step 1: Find outgoing edges from Chao Wu
out_edges_1 <- mc1_edges_clean %>%
filter(from == unique(chosen_node_1))
# Step 2: Identify neighbour node names
out_node_names_1 <- out_edges_1$to
# Step 1: Find outgoing edges from Chao Wu
out_edges_2 <- mc1_edges_clean %>%
filter(from == unique(chosen_node_2))
# Step 2: Identify neighbour node names
out_node_names_2 <- out_edges_2$to
# Step 1: Find outgoing edges from Chao Wu
out_edges_3 <- mc1_edges_clean %>%
filter(from == unique(chosen_node_3))
# Step 2: Identify neighbour node names
out_node_names_3 <- out_edges_3$to
# Step 1: Find outgoing edges from Chao Wu
out_edges_4 <- mc1_edges_clean %>%
filter(from == unique(chosen_node_4))
# Step 2: Identify neighbour node names
out_node_names_4 <- out_edges_4$to
# Step 1: Find outgoing edges from Chao Wu
out_edges_5 <- mc1_edges_clean %>%
filter(from == unique(chosen_node_5))
# Step 2: Identify neighbour node names
out_node_names_5 <- out_edges_5$to
# Build subgraph using names
sub_nodes <- unique(c(chosen_node_1,
chosen_node_2,
chosen_node_3,
chosen_node_4,
chosen_node_5,
out_node_names_1,
out_node_names_2,
out_node_names_3,
out_node_names_4,
out_node_names_5))
sub_graph <- graph %>%
activate(nodes) %>%
filter(name %in% sub_nodes)
g <- sub_graph %>%
ggraph(layout = "fr") +
geom_edge_fan(
aes(
edge_colour = `Edge Colour`,
start_cap = circle(1, 'mm'),
end_cap = circle(1, 'mm')
),
arrow = arrow(length = unit(1, 'mm')),
alpha = 0.3
) +
geom_point_interactive(
aes(
x = x,
y = y,
data_id = name,
colour = `Node Colour`,
shape = `Node Type`,
size = ifelse(`node_name` %in% c(chosen_node_1,
chosen_node_2,
chosen_node_3,
chosen_node_4,
chosen_node_5), 3, 1),
tooltip = case_when(
`Node Type` == "Album" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)", node_name, genre, notable, release_date
),
`Node Type` == "Song" ~ sprintf(
"%s<br/>%s<br/>Notable: %s<br/>(%s)<br/>Single: %s", node_name, genre, notable, release_date, single
),
TRUE ~ sprintf("%s", node_name)
)
),
show.legend = c(size = FALSE)
)+
geom_node_text(
aes(
label = ifelse(`node_name` == chosen_creator_1, chosen_creator_1,
ifelse(`node_name` == chosen_creator_2, chosen_creator_2,
ifelse(`node_name` == chosen_creator_3, chosen_creator_3,
ifelse(`node_name` == chosen_creator_4, chosen_creator_4,
ifelse(`node_name` == chosen_creator_5, chosen_creator_5, NA)))))
),
fontface = "bold",
size = 2.5,
colour = 'red',
show.legend = FALSE
) +
scale_shape_manual(
name = "Node Type",
values = c(
"Album" = 16,
"MusicalGroup" = 15,
"Person" = 17,
"Song" = 10
)
) +
scale_edge_colour_manual(
name = "Edge Colour",
values = c(
`Creator Of` = "#47D45A",
`Influenced By` = "#FF5757",
`Member Of` = "#CF57FF"
)
) +
scale_colour_manual(
name = "Node Colour",
values = c(
"Musician" = "grey50",
"Oceanus Folk" = "#0027EA",
"Other Genre" = "#A45200"
)
) +
theme_graph() +
theme(legend.text = element_text(size = 6),
legend.title = element_text(size = 9)) +
scale_size_identity()
girafe(ggobj = g, width_svg = 7, height_svg = 6)
Tip
- All five artists are solo artists and none of them are part of the same musical group
- Chao Wu, Xia Jia, Donna Caldwell and Xiulan Ye have some collaborative works with each other which can explain why some of their graphs overlaps.
- Chao Wu, Xia Jia, Donna Caldwell and Xiulan Ye produced Winds of the Basque Shore and Destiny’s Call together.
6.3.8 Predicting who the next three Oceanus Folk stars with be over the next five years
Sailor Shift
- Sailor Shift is ranked 1st in Oceanus Folk star factor.
- Per the VAST Challenge background, she is already one of music’s biggest superstars and a dominant figure in the Oceanus Folk community.
- Therefore, she will not be included in these predictions, as she has already achieved superstar status.
- This analysis will continue to identify the next 3 emerging artists poised to become the next Oceanus Folk stars.
Chao Wu
- Chao Wu is the second on the Star Factor list and his influence is large having influenced/collaborated with 190 Artists and influenced the creation of 44 Music with his Oceanus Folk music.
- Furthermore, he gained his large following despite having only released 4 music.
- Among his 4 music,3 of them are hits.
- His last Oceanus Folk work was in 2025 but his work is still being referred to in 2038.
Xia Jia
- Xia Jia is the next on the Star Factor list and her influence is equally large having influenced 178 Artists and 42 Music with her Oceanus Folk music.
- Furthermore, she has also gained this large following despite having only released 4 music.
- Similarly, 3 of them are hits.
- Her last Oceanus Folk work was in 2028 but her works were last referred to in 2030 which is less recent than Chao Wu.
Xiulan Ye
- Both Xiulan Ye and Donna Caldwell have produced the 2 influential songs Basque Shore and Destiny’s Call together.
- Their last Oceanus Folk work was in 2017 and was last referred to in 2030.
- However, Xiulan Ye is slightly more established in the music scene having also produced Unbound from the Doom Metal genre.
- Therefore, the third predicted star will be Xiulan Ye but Donna Caldwell has very good potential as well.
Prediction
In this part of our analysis, we set out to give three predictions of who the next Oceanus Folk stars with be over the next five years.
To do this, we designed a data-driven Star Factor score— a predictive measure using key metrics of an artist’s popularity and influence that capture what it means to be a rising star in the Oceanus Folk music scene:
Total Music Releases: How many works (songs/albums) the artist has produced.
Notable Music Releases: How many of those works are considered hits or critically notable.
Influenced Music Works: The number of downstream works (songs/albums) influenced by this artist’s creations.
Influenced Artists: The number of distinct artists who were directly or indirectly influenced by this artist.
These metrics were computed for every Oceanus Folk artist in the dataset.
library(purrr)
all_oceanus_creators <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
pull(creator_name) %>%
unique()
compute_creator_metrics <- function(creator_name) {
creator_node <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == !!creator_name) %>%
pull(creator_from) %>%
unique()
creator_songs <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_name == !!creator_name) %>%
pull(song_to) %>%
unique()
notable_count <- mc1_nodes_clean %>%
filter(name %in% creator_songs, notable == TRUE) %>%
nrow()
influenced_music <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% creator_node, `Edge Colour` == "Influenced By") %>%
pull(infuence_music_collaborate) %>%
unique() %>%
length()
influenced_artists <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_from %in% creator_node, influence_creator != creator_node) %>%
pull(influence_creator) %>%
unique() %>%
length()
tibble(
creator_name = creator_name,
total_music = length(creator_songs),
notable_music = notable_count,
influenced_music = influenced_music,
influenced_artists = influenced_artists
)
}Normalize all 4 columns to 0–1 scale
artist_metrics_df <- map_dfr(all_oceanus_creators, compute_creator_metrics)
artist_metrics_df <- artist_metrics_df %>%
mutate(
norm_total_music = (total_music - min(total_music)) / (max(total_music) - min(total_music)),
norm_notable_music = (notable_music - min(notable_music)) / (max(notable_music) - min(notable_music)),
norm_influenced_music = (influenced_music - min(influenced_music)) / (max(influenced_music) - min(influenced_music)),
norm_influenced_artists = (influenced_artists - min(influenced_artists)) / (max(influenced_artists) - min(influenced_artists)),
# Star Factor = Equal weighted average of all four metrics
star_score = 0.25 * norm_total_music +
0.25 * norm_notable_music +
0.25 * norm_influenced_music +
0.25 * norm_influenced_artists
)Filters the data to include only years 2030–2040.
Groups by artist and year.
For each (artist, year) combination, computes:
total_music: how many distinct songs they created that year. notable_music: how many were marked as notable. influenced_music: how many unique music works they influenced. influenced_artists: how many unique artists they influenced.
# Step 1: Build yearly metrics for Oceanus Folk creators (2030–2040)
artist_yearly_metrics <- oceanus_creator_and_songs_and_influences_and_creators_collaborate %>%
filter(creator_release_date >= 2030, creator_release_date <= 2040) %>%
group_by(creator_name, creator_release_date) %>%
summarise(
total_music = n_distinct(song_to),
notable_music = sum(notable == TRUE, na.rm = TRUE),
influenced_music = n_distinct(infuence_music_collaborate[`Edge Colour` == "Influenced By"], na.rm = TRUE),
influenced_artists = n_distinct(influence_creator[!is.na(influence_creator)], na.rm = TRUE),
.groups = "drop"
)Compute the trend slope of each metric over time per artist
Fit a linear regression model for each metric across years (y ~ year). Extract the slope (rate of change per year).
For each artist:
It calculates the annual trend (i.e., slope) of each metric from 2030 to 2040. If an artist has no data for some years, NA is filled with 0.
library(purrr)
compute_trend_slope <- function(df, metric) {
if (nrow(df) < 2) return(NA) # Not enough years of data
model <- lm(reformulate("creator_release_date", metric), data = df)
coef(model)[["creator_release_date"]]
}
# Compute slope of trend over time for each artist
trend_df <- artist_yearly_metrics %>%
group_by(creator_name) %>%
summarise(
trend_music = compute_trend_slope(pick(everything()), "total_music"),
trend_notable = compute_trend_slope(pick(everything()), "notable_music"),
trend_influenced_music = compute_trend_slope(pick(everything()), "influenced_music"),
trend_influenced_artists = compute_trend_slope(pick(everything()), "influenced_artists"),
.groups = "drop"
) %>%
replace_na(list(
trend_music = 0,
trend_notable = 0,
trend_influenced_music = 0,
trend_influenced_artists = 0
))Joins the trend slopes to the base dataset artist_metrics_df, which already contains each artist’s cumulative star_score (as of 2040).
Calculates an average trend across the 4 metrics.
Projects the star score 5 years into the future (2045) using “predicted_star_score = star_score (in 2040) + 5 × average trend per year”
# Merge current score (2040) with trend data
predicted_star_df <- artist_metrics_df %>%
left_join(trend_df, by = "creator_name") %>%
mutate(
# Average slope of the 4 metrics
trend_avg = (trend_music + trend_notable + trend_influenced_music + trend_influenced_artists) / 4,
# Predict star score in 2045 assuming 5 years of continued trend
predicted_star_score = star_score + 5 * trend_avg
) %>%
arrange(desc(predicted_star_score))predicted_star_df %>%
select(creator_name, star_score, trend_avg, predicted_star_score) %>%
head(10) %>%
kable(format = "html", digits = 2, caption = "Top 10 Predicted Oceanus Folk Stars in 2045") %>%
kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"), full_width = FALSE)| creator_name | star_score | trend_avg | predicted_star_score |
|---|---|---|---|
| Kai Reynolds | 0.05 | 0.75 | 3.80 |
| Maya Jensen | 0.10 | 0.37 | 1.97 |
| Sophie Ramirez | 0.10 | 0.30 | 1.60 |
| Sailor Shift | 0.55 | 0.05 | 0.81 |
| Tidal Reverie | 0.06 | 0.12 | 0.68 |
| Coralia Bellweather | 0.09 | 0.00 | 0.09 |
| Levi Holloway | 0.07 | 0.00 | 0.07 |
| Jie Li | 0.07 | 0.00 | 0.07 |
| Marin Thorne | 0.07 | 0.00 | 0.07 |
| Jonah Calloway | 0.07 | 0.00 | 0.07 |